Unusual ß1-4-galactosidase activity of an α1-6-mannosidase from Xanthomonas manihotis in the processing of branched hybrid and complex glycans.

Mannosidases are a diverse group of glycoside hydrolases that play crucial roles in mannose trimming of oligomannose glycans, glycoconjugates, and glycoproteins involved in numerous cellular processes, such as glycan biosynthesis and metabolism, structure regulation, cellular recognition, and cell-pathogen interactions. Exomannosidases and endomannosidases cleave specific glycosidic bonds of mannoside linkages in glycans and can be used in enzyme-based methods for sequencing of isomeric glycan structures. α1-6-mannosidase from Xanthomonas manihotis is known as a highly specific exoglycosidase that removes unbranched α1-6 linked mannose residues from oligosaccharides. However, we discovered that this α1-6-mannosidase also possesses an unexpected ß1-4-galactosidase activity in the processing of branched hybrid and complex glycans through our use of enzymatic reactions, high performance anion-exchange chromatography, and liquid chromatography mass spectrometric sequencing. Our docking simulation of the α1-6-mannosidase with glycan substrates reveals potential interacting residues in a relatively shallow pocket slightly differing from its homologous enzymes in the glycoside hydrolase 125 family, which may be responsible for the observed higher promiscuity in substrate binding and subsequent terminal glycan hydrolysis. This observation of novel ß1-4-galactosidase activity of the α1-6-mannosidase provides unique insights into its bifunctional activity on the substrate structure-dependent processing of terminal α1-6-mannose of unbranched glycans and terminal ß1-4-galactose of hybrid and complex glycans. The finding thus suggests the dual glycosidase specificity of this α1-6-mannosidase and the need for careful consideration when used for the structural elucidation of glycan isomers.

Employment status, productivity loss, and associated factors among people with multiple sclerosis.

BACKGROUND: Multiple Sclerosis (MS) affects people in their most productive years of life. Consequently, MS can substantially affect employment and work-related outcomes. OBJECTIVES: This study characterizes productivity loss and employment status of people with multiple sclerosis (pwMS) and investigates associated factors. METHODS: We used baseline data collected as part of the Canadian Prospective Cohort Study to Understand Progression in Multiple Sclerosis (CanProCo). Using the Valuation of Lost Productivity questionnaire, we measured MS-related paid work productivity loss for those employed, productivity losses incurred by those unemployed (i.e. lost employment time), and unpaid work productivity losses for all. A set of sociodemographic, disease, and performance-related factors were investigated using a two-part regression model for productivity loss and a multinomial logistic model for employment status. RESULTS: From the cohort of 888 pwMS enrolled at baseline (mostly showing mild to moderate disability), 75% were employed, and of those unemployed, 69% attributed their unemployment to health-related issues. Total productivity loss over a 3-month period averaged 64 and 395 hours for those employed and unemployed, respectively. Some factors that affected productivity loss and employment status included use of disease-modifying therapies, fatigue, and performance indicators such as cognitive processing speed. CONCLUSION: Productivity loss experienced by employed and unemployed pwMS is substantial. Targeting the identified modifiable factors is likely to improve work productivity and permanence of MS patients in the workforce.

Brain Imaging Abnormalities in Mixed Alzheimer's and Subcortical Vascular Dementia.

BACKGROUND: A large proportion of Alzheimer's disease (AD) patients have coexisting subcortical vascular dementia (SVaD), a condition referred to as mixed dementia (MixD). Brain imaging features of MixD presumably include those of cerebrovascular disease and AD pathology, but are difficult to characterize due to their heterogeneity. OBJECTIVE: To perform an exploratory analysis of conventional and non-conventional structural magnetic resonance imaging (MRI) abnormalities in MixD and to compare them to those observed in AD and SVaD. METHODS: We conducted a cross-sectional, region-of-interest-based analysis of 1) hyperintense white-matter signal abnormalities (WMSA) on T2-FLAIR and hypointense WMSA on T1-weighted MRI; 2) diffusion tensor imaging; 3) quantitative susceptibility mapping; and 4) effective transverse relaxation rate (R2*) in N = 17 participants (AD:5, SVaD:5, MixD:7). General linear model was used to explore group differences in these brain imaging measures. RESULTS: Model findings suggested imaging characteristics specific to our MixD group, including 1) higher burden of WMSAs on T1-weighted MRI (versus both AD and SVaD); 2) frontal lobar preponderance of WMSAs on both T2-FLAIR and T1-weighted MRI; 3) higher fractional anisotropy values within normal-appear white-matter tissues (versus SVaD, but not AD); and 4) lower R2* values within the T2-FLAIR WMSA areas (versus both AD and SVaD). CONCLUSION: These findings suggest a preliminary picture of the location and type of brain imaging characteristics associated with MixD. Future imaging studies may employ region-specific hypotheses to distinguish MixD more rigorously from AD or SVaD.

A data-driven T2 relaxation analysis approach for myelin water imaging: Spectrum analysis for multiple exponentials via experimental condition oriented simulation (SAME-ECOS).

PURPOSE: The decomposition of multi-exponential decay data into a T2 spectrum poses substantial challenges for conventional fitting algorithms, including non-negative least squares (NNLS). Based on a combination of the resolution limit constraint and machine learning neural network algorithm, a data-driven and highly tailorable analysis method named spectrum analysis for multiple exponentials via experimental condition oriented simulation (SAME-ECOS) was proposed. THEORY AND METHODS: The theory of SAME-ECOS was derived. Then, a paradigm was presented to demonstrate the SAME-ECOS workflow, consisting of a series of calculation, simulation, and model training operations. The performance of the trained SAME-ECOS model was evaluated using simulations and six in vivo brain datasets. The code is available at https://github.com/hanwencat/SAME-ECOS. RESULTS: Using NNLS as the baseline, SAME-ECOS achieved over 15% higher overall cosine similarity scores in producing the T2 spectrum, and more than 10% lower mean absolute error in calculating the myelin water fraction (MWF), as well as demonstrated better robustness to noise in the simulation tests. Applying to in vivo data, MWF from SAME-ECOS and NNLS was highly correlated among all study participants. However, a distinct separation of the myelin water peak and the intra/extra-cellular water peak was only observed in the mean T2 spectra determined using SAME-ECOS. In terms of data processing speed, SAME-ECOS is approximately 30 times faster than NNLS, achieving a whole-brain analysis in 3 min. CONCLUSION: Compared with NNLS, the SAME-ECOS method yields much more reliable T2 spectra in a dramatically shorter time, increasing the feasibility of multi-component T2 decay analysis in clinical settings.

Productivity loss among people with early multiple sclerosis: A Canadian study.

OBJECTIVES: To analyze work productivity loss and costs, including absenteeism (time missed from work), presenteeism (reduced productivity while working), and unpaid work loss, among a sample of employed people with multiple sclerosis (pwMS) in Canada, as well as its association with clinical, sociodemographic, and work-related factors. METHODS: We used cross-sectional data collected as part of the Canadian Prospective Cohort Study to Understand Progression in MS (CanProCo) and information from the Valuation of Lost Productivity questionnaire. RESULTS: Among 512 pwMS who were employed, 97% showed no or mild disability and 55% experienced productivity loss due to MS in the prior 3 months. Total productivity time loss over a 3-month period averaged 60 hours (SD = 107; 23 from presenteeism, 19 from absenteeism, and 18 from unpaid work), leading to a mean cost of lost productivity of CAD$2480 (SD = 4282) per patient, with an hourly paid productivity loss greater than the wage loss. Fatigue retained significant associations with all productivity loss outcomes. CONCLUSION: Unpaid work loss and productivity losses exceeding those of the employee alone (due to teamwork and associated factors) are key additional contributors of the high economic burden of MS. Workplace accommodations and treatments targeted at fatigue could lessen the economic impact of MS.

Characterization of multiple sclerosis neuroinflammation and neurodegeneration with relaxation and diffusion basis spectrum imaging.

BACKGROUND: Advanced magnetic resonance imaging (MRI) methods can provide more specific information about various microstructural tissue changes in multiple sclerosis (MS) brain. Quantitative measurement of T1 and T2 relaxation, and diffusion basis spectrum imaging (DBSI) yield metrics related to the pathology of neuroinflammation and neurodegeneration that occurs across the spectrum of MS. OBJECTIVE: To use relaxation and DBSI MRI metrics to describe measures of neuroinflammation, myelin and axons in different MS subtypes. METHODS: 103 participants (20 clinically isolated syndrome (CIS), 33 relapsing-remitting MS (RRMS), 30 secondary progressive MS and 20 primary progressive MS) underwent quantitative T1, T2, DBSI and conventional 3T MRI. Whole brain, normal-appearing white matter, lesion and corpus callosum MRI metrics were compared across MS subtypes. RESULTS: A gradation of MRI metric values was seen from CIS to RRMS to progressive MS. RRMS demonstrated large oedema-related differences, while progressive MS had the most extensive abnormalities in myelin and axonal measures. CONCLUSION: Relaxation and DBSI-derived MRI measures show differences between MS subtypes related to the severity and composition of underlying tissue damage. RRMS showed oedema, demyelination and axonal loss compared with CIS. Progressive MS had even more evidence of increased oedema, demyelination and axonal loss compared with CIS and RRMS.

Deep grey matter injury in multiple sclerosis: a NAIMS consensus statement.

Although multiple sclerosis has traditionally been considered a white matter disease, extensive research documents the presence and importance of grey matter injury including cortical and deep regions. The deep grey matter exhibits a broad range of pathology and is uniquely suited to study the mechanisms and clinical relevance of tissue injury in multiple sclerosis using magnetic resonance techniques. Deep grey matter injury has been associated with clinical and cognitive disability. Recently, MRI characterization of deep grey matter properties, such as thalamic volume, have been tested as potential clinical trial end points associated with neurodegenerative aspects of multiple sclerosis. Given this emerging area of interest and its potential clinical trial relevance, the North American Imaging in Multiple Sclerosis (NAIMS) Cooperative held a workshop and reached consensus on imaging topics related to deep grey matter. Herein, we review current knowledge regarding deep grey matter injury in multiple sclerosis from an imaging perspective, including insights from histopathology, image acquisition and post-processing for deep grey matter. We discuss the clinical relevance of deep grey matter injury and specific regions of interest within the deep grey matter. We highlight unanswered questions and propose future directions, with the aim of focusing research priorities towards better methods, analysis, and interpretation of results.

Painting by lesions: White matter hyperintensities disrupt functional networks and global cognition.

White matter hyperintensities (WMH) are a prominent feature of cerebral small vessel disease and are associated with cognitive impairment. These deficits in cognition may be caused by the disruption of large-scale functional networks due to the presence of WMHs. However, knowledge regarding the relevance of these lesions on functional networks remains inconclusive. These inconsistencies may derive from issues with interpreting functional imaging data from clinical populations. Lesion network mapping is a technique that allows the overlaying of lesions from a patient population to the functional connectivity of a human connectome derived from healthy adults. This allows researchers to identify functional networks that would be disrupted in a healthy population should the WMHs seen in cerebral small vessel disease be present. We hypothesized that the extent to which these functional networks are disrupted by WMHs is associated with cognitive performance in older adults with cerebral small vessel disease. This cross-sectional study combined baseline data from four studies to create a total sample of 164 older adults (aged ≥55) from metropolitan Vancouver with cerebral small vessel disease. Using lesion network mapping, we assessed the percentage overlap between voxels functionally connected with both the WMHs (lesion network) and five common functional networks: (1) visual; (2) dorsal attention; (3) ventral attention; (4) sensorimotor; and (5) frontoparietal. Cognition was assessed using: (1) Montreal Cognitive Assessment (MoCA); (2) Stroop Colour Word Test (3-2); (3) Trail Making Tests (Part B-A); and (4) Digit Symbol Substitution Test. A One-Way ANOVA and Tukey post-hoc tests were performed to identify the functional networks with greatest percentage overlap with the lesion network. Partial correlations controlling for age were used to analyse whether the extent of the overlap between the lesion and functional networks was associated with poorer cognition. The visual, ventral attention, and frontoparietal networks had significantly greater overlap with the lesion network. After controlling for multiple comparisons, level of lesion network overlap with both the sensorimotor network (p<.001) and ventral attention network (p <. 001) was significantly correlated with MoCA score. Thus, the greater the disruption to the sensorimotor and ventral attention networks, the poorer the global cognition. Our results reveal that the visual, ventral attention, and frontoparietal networks are most vulnerable to disruptions stemming from WMHs. Additionally, we identified that disruption to the sensorimotor and ventral attention networks, as a result of WMHs, may underlie deficits in global cognition in older adults with cerebral small vessel disease.

Cervical cord myelin abnormality is associated with clinical disability in multiple sclerosis.

BACKGROUND: Myelin water imaging (MWI) was recently optimized to provide quantitative in vivo measurement of spinal cord myelin, which is critically involved in multiple sclerosis (MS) disability. OBJECTIVE: To assess cervical cord myelin measurements in relapsing-remitting multiple sclerosis (RRMS) and progressive multiple sclerosis (ProgMS) participants and evaluate the correlation between myelin measures and clinical disability. METHODS: We used MWI data from 35 RRMS, 30 ProgMS, and 28 healthy control (HC) participants collected at cord level C2/C3 on a 3 T magnetic resonance imaging (MRI) scanner. Myelin heterogeneity index (MHI), a measurement of myelin variability, was calculated for whole cervical cord, global white matter, dorsal column, lateral and ventral funiculi. Correlations were assessed between MHI and Expanded Disability Status Scale (EDSS), 9-Hole Peg Test (9HPT), timed 25-foot walk, and disease duration. RESULTS: In various regions of the cervical cord, ProgMS MHI was higher compared to HC (between 9.5% and 31%, p ⩽ 0.04) and RRMS (between 13% and 26%, p ⩽ 0.02), and ProgMS MHI was associated with EDSS (r = 0.42-0.52) and 9HPT (r = 0.45-0.52). CONCLUSION: Myelin abnormalities within clinically eloquent areas are related to clinical disability. MWI metrics have a potential role for monitoring subclinical disease progression and adjudicating treatment efficacy for new therapies targeting ProgMS.

The Canadian prospective cohort study to understand progression in multiple sclerosis (CanProCo): rationale, aims, and study design.

BACKGROUND: Neurological disability progression occurs across the spectrum of people living with multiple sclerosis (MS). Although there are a handful of disease-modifying treatments approved for use in progressive phenotypes of MS, there are no treatments that substantially modify the course of clinical progression in MS. Characterizing the determinants of clinical progression can inform the development of novel therapeutic agents and treatment approaches that target progression in MS, which is one of the greatest unmet needs in clinical practice. Canada, having one of the world's highest rates of MS and a publicly-funded health care system, represents an optimal country to achieve in-depth analysis of progression. Accordingly, the overarching aim of the Canadian Prospective Cohort Study to Understand Progression in MS (CanProCo) is to evaluate a wide spectrum of factors associated with the clinical onset and rate of disease progression in MS, and to describe how these factors relate to one another to influence progression. METHODS: CanProCo is a prospective, observational cohort study with investigators specializing in epidemiology, neuroimaging, neuroimmunology, health services research and health economics. CanProCo's study design was approved by an international review panel, comprised of content experts and key stakeholders. One thousand individuals with radiologically-isolated syndrome, relapsing-remitting MS, and primary-progressive MS within 10-15 years of disease onset will be recruited from 5 academic MS centres in Canada. Participants will undergo detailed clinical evaluation annually over 5 years (including advanced, app-based clinical data collection). In a subset of participants within 5-10 years of disease onset (n = 500), blood, cerebrospinal fluid, and research MRIs will be collected allowing an integrated, in-depth evaluation of factors contributing to progression in MS from multiple perspectives. Factors of interest range from biological measures (e.g. single-cell RNA-sequencing), MRI-based microstructural assessment, participant characteristics (self-reported, performance-based, clinician-assessed, health-system based), and micro and macro-environmental factors. DISCUSSION: Halting the progression of MS remains a fundamental need to improve the lives of people living with MS. Achieving this requires leveraging transdisciplinary approaches to better characterize why clinical progression occurs. CanProCo is a pioneering multi-dimensional cohort study aiming to characterize these determinants to inform the development and implementation of efficacious and effective interventions.

Myelin water imaging data analysis in less than one minute.

PURPOSE: Based on a deep learning neural network (NN) algorithm, a super fast and easy to implement data analysis method was proposed for myelin water imaging (MWI) to calculate the myelin water fraction (MWF). METHODS: A NN was constructed and trained on MWI data acquired by a 32-echo 3D gradient and spin echo (GRASE) sequence. Ground truth labels were created by regularized non-negative least squares (NNLS) with stimulated echo corrections. Voxel-wise GRASE data from 5 brains (4 healthy, 1 multiple sclerosis (MS)) were used for NN training. The trained NN was tested on 2 healthy brains, 1 MS brain with segmented lesions, 1 healthy spinal cord, and 1 healthy brain acquired from a different scanner. RESULTS: Production of whole brain MWF maps in approximately 33 â€‹s can be achieved by a trained NN without graphics card acceleration. For all testing regions, no visual differences between NN and NNLS MWF maps were observed, and no obvious regional biases were found. Quantitatively, all voxels exhibited excellent agreement between NN and NNLS (all R2>0.98, p â€‹< â€‹0.001, mean absolute error <0.01). CONCLUSION: The time for accurate MWF calculation can be dramatically reduced to less than 1 â€‹min by the proposed NN, addressing one of the barriers facing future clinical feasibility of MWI.

Resolving Isomeric Structures of Native Glycans by Nanoflow Porous Graphitized Carbon Chromatography-Mass Spectrometry.

Characterization of the structural diversity of glycans by liquid chromatography-tandem mass spectrometry (LC-MS/MS) remains an analytical challenge in large-scale glycomics applications because of the presence of heterogeneous composition, ubiquitous isomers, lability of post-translational glycan modifications, and complexity of data interpretation. High-resolution separation of glycan isomers differentiating from positional, linkage, branching, and anomeric structures is often a prerequisite to ensure the comprehensive glycan identification. Here, we developed a straightforward method using self-packed capillary porous graphitic carbon (PGC) columns for nanoflow LC-MS/MS analyses of native glycans released from glycoproteins. The technique enables highly resolved chromatographic separation of over 20 high-mannose glycan isomers in ribonuclease B and a diverse range of hybrid and complex-type sialoglycoforms of fetuin. The distinct structures of anomeric glycans and linkage sialoglycan isomers, α2,3 and α2,6, were identified by the characteristic MS/MS fragment ions. A glycan sequencing strategy utilizing diagnostic ions and complementary fragments specific to branching residues was established to simplify the MS/MS data interpretation of closely related isomeric structures. To promote the PGC-LC-MS/MS-based method for glycome-wide applications, we extended analyses to native sulfoglycans from the egg-propagated and cell culture-derived influenza vaccines and demonstrate the high-resolution separation and structural characterization of underivatized neutral and anionic glycoforms including oligomannosidic glycan anomers, sialoglycan linkage isomers, and regioisomers of afucosylated and fucosylated sulfoglycans containing sulfated-6-GlcNAc and sulfated-4-GalNAc residues.

Quantitative neuroimaging measures of myelin in the healthy brain and in multiple sclerosis.

Quantitative magnetic resonance imaging (MRI) techniques have been developed as imaging biomarkers, aiming to improve the specificity of MRI to underlying pathology compared to conventional weighted MRI. For assessing the integrity of white matter (WM), myelin, in particular, several techniques have been proposed and investigated individually. However, comparisons between these methods are lacking. In this study, we compared four established myelin-sensitive MRI techniques in 56 patients with relapsing-remitting multiple sclerosis (MS) and 38 healthy controls. We used T2-relaxation with combined GRadient And Spin Echoes (GRASE) to measure myelin water fraction (MWF-G), multi-component driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) to measure MWF-D, magnetization-transfer imaging to measure magnetization-transfer ratio (MTR), and T1 relaxation to measure quantitative T1 (qT1 ). Using voxelwise Spearman correlations, we tested the correspondence of methods throughout the brain. All four methods showed associations that varied across tissue types; the highest correlations were found between MWF-D and qT1 (median ρ across tissue classes 0.8) and MWF-G and MWF-D (median ρ = 0.59). In eight WM tracts, all measures showed differences (p < 0.05) between MS normal-appearing WM and healthy control WM, with qT1 showing the highest number of different regions (8), followed by MWF-D and MTR (6), and MWF-G (n = 4). Comparing the methods in terms of their statistical sensitivity to MS lesions in WM, MWF-D demonstrated the best accuracy (p < 0.05, after multiple comparison correction). To aid future power analysis, we provide the average and standard deviation volumes of the four techniques, estimated from the healthy control sample.

Three-dimensional MRI sequences in MS diagnosis and research.

The most recent guidelines for magnetic resonance imaging (MRI) in multiple sclerosis (MS) recommend three-dimensional (3D) MRI sequences over their two-dimensional (2D) counterparts. This development has been made possible by advances in MRI scanner hardware and software. In this article, we review the 3D versions of conventional sequences, including T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR), as well as more advanced scans, including double inversion recovery (DIR), FLAIR2, FLAIR*, phase-sensitive inversion recovery, and susceptibility weighted imaging (SWI).

A 24-month advanced magnetic resonance imaging study of multiple sclerosis patients treated with alemtuzumab.

BACKGROUND: Tissue damage in both multiple sclerosis (MS) lesions and normal-appearing white matter (NAWM) are important contributors to disability and progression. Specific aspects of MS pathology can be measured using advanced imaging. Alemtuzumab is a humanised monoclonal antibody targeting CD52 developed for MS treatment. OBJECTIVE: To investigate changes over 2 years of advanced magnetic resonance (MR) metrics in lesions and NAWM of MS patients treated with alemtuzumab. METHODS: A total of 42 relapsing-remitting alemtuzumab-treated MS subjects were scanned for 2 years at 3 T. T1 relaxation, T2 relaxation, diffusion tensor, MR spectroscopy and volumetric sequences were performed. Mean T1 and myelin water fraction (MWF) were determined for stable lesions, new lesions and NAWM. Fractional anisotropy was calculated for the corpus callosum (CC) and N-acetylaspartate (NAA) concentration was determined from a large NAWM voxel. Brain parenchymal fraction (BPF), cortical thickness and CC area were also calculated. RESULTS: No change in any MR measurement was found in lesions or NAWM over 24 months. BPF, cortical thickness and CC area all showed decreases in the first year followed by stability in the second year. CONCLUSION: Advanced MR biomarkers of myelin (MWF) and neuron/axons (NAA) show no change in NAWM over 24 months in alemtuzumab-treated MS participants.

Engineering Cellular Microenvironments with Photo- and Enzymatically Responsive Hydrogels: Toward Biomimetic 3D Cell Culture Models.

Conventional cell culture techniques using 2D polystyrene or glass have provided great insight into key biochemical mechanisms responsible for cellular events such as cell proliferation, differentiation, and cell-cell interactions. However, the physical and chemical properties of 2D culture in vitro are dramatically different than those found in the native cellular microenvironment in vivo. Cells grown on 2D substrates differ significantly from those grown in vivo, and this explains, in part, why many promising drug candidates discovered through in vitro drug screening assays fail when they are translated to in vivo animal or human models. To overcome this obstacle, 3D cell culture using biomimetic hydrogels has emerged as an alternative strategy to recapitulate native cell growth in vitro. Hydrogels, which are water-swollen polymers, can be synthetic or naturally derived. Many methods have been developed to control the physical and chemical properties of the hydrogels to match those found in specific tissues. Compared to 2D culture, cells cultured in 3D gels with the appropriate physicochemical cues can behave more like they naturally do in vivo. While conventional hydrogels involve modifications to the bulk material to mimic the static aspects of the cellular microenvironment, recent progress has focused on using more dynamic hydrogels, the chemical and physical properties of which can be altered with external stimuli to better mimic the dynamics of the native cellular microenvironment found in vivo. In this Account, we describe our progress in designing stimuli-responsive, optically transparent hydrogels that can be used as biomimetic extracellular matrices (ECMs) to study cell differentiation and migration in the context of modeling the nervous system and cancer. Specifically, we developed photosensitive agarose and hyaluronic acid hydrogels that are activated by single or two-photon irradiation for biomolecule immobilization at specific volumes within the 3D hydrogel. By controlling the spatial location of protein immobilization, we created 3D patterns and protein concentration gradients within these gels. We used the latter to study the effect of VEGF-165 concentration gradients on the interactions between endothelial cells and retinal stem cells. Hyaluronic acid (HA) is particularly compelling as it is naturally found in the ECM of many tissues and the tumor microenvironment. We used Diels-Alder click chemistry and cryogelation to alter the chemical and physical properties of these hydrogels. We also designed HA hydrogels to study the invasion of breast cancer cells. HA gels were chemically cross-linked with matrix metalloproteinase (MMP)-degradable peptides that degrade in the presence of cancer cell-secreted MMPs, thus allowing cells to remodel their local microenvironment and invade into HA/MMP-degradable gels.

Diels-Alder Click-Cross-Linked Hydrogels with Increased Reactivity Enable 3D Cell Encapsulation.

Engineered hydrogels have been extensively used to direct cell function in 3D cell culture models, which are more representative of the native cellular microenvironment than conventional 2D cell culture. Previously, hyaluronan-furan and bis-maleimide polyethylene glycol hydrogels were synthesized via Diels-Alder chemistry at acidic pH, which did not allow encapsulation of viable cells. In order to enable gelation at physiological pH, the reaction kinetics were accelerated by replacing the hyaluronan-furan with the more electron-rich hyaluronan-methylfuran. These new click-cross-linked hydrogels gel faster and at physiological pH, enabling encapsulation of viable cells, as demonstrated with 3D culture of 5 different cancer cell lines. The methylfuran accelerates Diels-Alder cycloaddition yet also increases the retro Diels-Alder reaction. Using computational analysis, we gain insight into the mechanism of the increased Diels-Alder reactivity and uncover that transition state geometry and an unexpected hydrogen-bonding interaction are important contributors to the observed rate enhancement. This cross-linking strategy serves as a platform for bioconjugation and hydrogel synthesis for use in 3D cell culture and tissue engineering.

Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology.

Artificial intelligence (AI) is rapidly moving from an experimental phase to an implementation phase in many fields, including medicine. The combination of improved availability of large datasets, increasing computing power, and advances in learning algorithms has created major performance breakthroughs in the development of AI applications. In the last 5 years, AI techniques known as deep learning have delivered rapidly improving performance in image recognition, caption generation, and speech recognition. Radiology, in particular, is a prime candidate for early adoption of these techniques. It is anticipated that the implementation of AI in radiology over the next decade will significantly improve the quality, value, and depth of radiology's contribution to patient care and population health, and will revolutionize radiologists' workflows. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI working group with the mandate to discuss and deliberate on practice, policy, and patient care issues related to the introduction and implementation of AI in imaging. This white paper provides recommendations for the CAR derived from deliberations between members of the AI working group. This white paper on AI in radiology will inform CAR members and policymakers on key terminology, educational needs of members, research and development, partnerships, potential clinical applications, implementation, structure and governance, role of radiologists, and potential impact of AI on radiology in Canada.

Spinal cord grey matter segmentation challenge.

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication.

Rapid myelin water imaging in human cervical spinal cord.

PURPOSE: Myelin water imaging (MWI) using multi-echo T2 relaxation is a quantitative MRI technique that can be used as an in vivo biomarker for myelin in the central nervous system. MWI using a multi-echo spin echo sequence currently takes more than 20 min to acquire eight axial slices (5 mm thickness) in the cervical spinal cord, making spinal cord MWI impractical for implementation in clinical studies. METHODS: In this study, an accelerated gradient and spin echo sequence (GRASE), previously validated for brain MWI, was adapted for spinal cord MWI. Ten healthy volunteers were scanned with the GRASE sequence (acquisition time 8.5 min) and compared with the multi-echo spin echo sequence (acquisition time 23.5 min). RESULTS: Using region of interest analysis, myelin estimates obtained from the two sequences were found to be in good agreement (mean difference = -0.0092, 95% confidence interval = - 0.0092 ± 0.061; regression slope = 1.01, ρ = 0.9). MWI using GRASE was shown to be highly reproducible with an average coefficient of variation of 6.1%. CONCLUSION: The results from this study show that MWI can be performed in the cervical spinal cord in less than 10 min, allowing for practical implementation in multimodal clinical studies. Magn Reson Med 78:1482-1487, 2017. © 2016 International Society for Magnetic Resonance in Medicine.