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ObjectiveTo investigate the results of real-world application of non-myeloablative autologous HSCT for multiple sclerosis (MS).MethodsBetween July 2003 and October 2019 at a single center (Northwestern University), 414 patients with relapsing remitting MS (RRMS) and 93 patients with newly diagnosed secondary progressive MS (SPMS) underwent non-myeloablative HSCT.ResultsThere was one treatment-related death (0.19%) due to hospital-acquired legionella pneumonia, and one patient developed neutropenic bacteremia (Klebsiella pneumonia) without sepsis. Overall 5-year survival was 98.8%. Post HSCT secondary autoimmune diseases (2nd ADs) were idiopathic thrombocytopenia (ITP) and hypo or hyperthyroidism. ITP was highest with alemtuzumab (14%) and 0 to 2.8% for the non-alemtuzumab regimens. After HSCT, 16 patients developed hypothyroidism (3.5%) and 15 developed hyperthyroidism / Grave’s disease (3.3%). Relapse free survival (RFS) at 5 years for RRMS and SPMS was 80.1% and 98.1%, respectively, while progression free survival (PFS) at 4 years for RRMS and SPMS was 95% versus 66%, respectively. For patients with RRMS, the EDSS significantly improved (p < 0.0001) at each follow-up from a pre-HSCT mean of 3.87 to 2.51, 2.50, 2.41, 2.33, and 2.19 at 1, 2, 3, 4, and 5 years, respectively. For SPMS, the EDSS improved significantly only at 1 year but not thereafter. For SPMS, the mean baseline EDSS of 5.09 changed post-HSCT to 4.85 (p = 0.04), 4.88 (p = 0.2), 4.92 (p = .27), 4.72 (p = 0.07), and 4.2 (p = 0.21) at 1, 2, 3, 4, 5 years, respectively.ConclusionIn patients with RRMS, autologous non-myeloablative HSCT is an effective one-time therapy, while HSCT appears of less benefit for newly diagnosed SPMS.

Summary Major polyamines include putrescine, spermidine, spermine and thermospermine, which play vital roles in growth and adaptation against environmental changes in plants. Thermospermine (T‐Spm) is synthetised by ACL5. The function of ACL5 in rice is still unknown. In this study, we used a reverse genetic strategy to investigate the biological function of OsACL5. We generated several knockout mutants by pYLCRISPR/Cas9 system and overexpressing (OE) lines of OsACL5. Interestingly, the OE plants exhibited environmentally‐dependent leaf rolling, smaller grains, lighter 1000‐grain weight and reduction in yield per plot. The area of metaxylem vessels of roots and leaves of OE plants were significantly smaller than those of WT, which possibly caused reduction in leaf water potential, resulting in leaf rolling with rise in the environmental temperature and light intensity and decrease in humidity. Additionally, the T‐Spm contents were markedly increased by over ninefold whereas the ethylene evolution was reduced in OE plants, suggesting that T‐Spm signalling pathway interacts with ethylene pathway to regulate multiple agronomic characters. Moreover, the osacl5 exhibited an increase in grain length, 1000‐grain weight, and yield per plot. OsACL5 may affect grain size via mediating the expression of OsDEP1, OsGS3 and OsGW2. Furthermore, haplotypes analysis indicated that OsACL5 plays a conserved function on regulating T‐Spm levels during the domestication of rice. Our data demonstrated that identification of OsACL5 provides a theoretical basis for understanding the physiological mechanism of T‐Spm which may play roles in triggering environmentally dependent leaf rolling; OsACL5 will be an important gene resource for molecular breeding for higher yield.

Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research. [Display omitted]

Cluster-extent based thresholding is currently the most popular method for multiple comparisons correction of statistical maps in neuroimaging studies, due to its high sensitivity to weak and diffuse signals. However, cluster-extent based thresholding provides low spatial specificity; researchers can only infer that there is signal somewhere within a significant cluster and cannot make inferences about the statistical significance of specific locations within the cluster. This poses a particular problem when one uses a liberal cluster-defining primary threshold (i.e., higher p-values), which often produces large clusters spanning multiple anatomical regions. In such cases, it is impossible to reliably infer which anatomical regions show true effects. From a survey of 814 functional magnetic resonance imaging (fMRI) studies published in 2010 and 2011, we show that the use of liberal primary thresholds (e.g., p<.01) is endemic, and that the largest determinant of the primary threshold level is the default option in the software used. We illustrate the problems with liberal primary thresholds using an fMRI dataset from our laboratory (N=33), and present simulations demonstrating the detrimental effects of liberal primary thresholds on false positives, localization, and interpretation of fMRI findings. To avoid these pitfalls, we recommend several analysis and reporting procedures, including 1) setting primary p<.001 as a default lower limit; 2) using more stringent primary thresholds or voxel-wise correction methods for highly powered studies; and 3) adopting reporting practices that make the level of spatial precision transparent to readers. We also suggest alternative and supplementary analysis methods. •Cluster-extent based thresholding is popular because of its high sensitivity.•However, cluster-extent based thresholding has several important problems.•One pitfall is low spatial specificity when significant clusters are large.•Another pitfall is increased false positives when a liberal primary threshold is used.•We recommend using stringent primary thresholds and augmented reporting procedures.

Total intracranial volume (TIV/ICV) is an important covariate for volumetric analyses of the brain and brain regions, especially in the study of neurodegenerative diseases, where it can provide a proxy of maximum pre-morbid brain volume. The gold-standard method is manual delineation of brain scans, but this requires careful work by trained operators. We evaluated Statistical Parametric Mapping 12 (SPM12) automated segmentation for TIV measurement in place of manual segmentation and also compared it with SPM8 and FreeSurfer 5.3.0. For T1-weighted MRI acquired from 288 participants in a multi-centre clinical trial in Alzheimer's disease we find a high correlation between SPM12 TIV and manual TIV (R2=0.940, 95% Confidence Interval (0.924, 0.953)), with a small mean difference (SPM12 40.4±35.4ml lower than manual, amounting to 2.8% of the overall mean TIV in the study). The correlation with manual measurements (the key aspect when using TIV as a covariate) for SPM12 was significantly higher (p<0.001) than for either SPM8 (R2=0.577 CI (0.500, 0.644)) or FreeSurfer (R2=0.801 CI (0.744, 0.843)). These results suggest that SPM12 TIV estimates are an acceptable substitute for labour-intensive manual estimates even in the challenging context of multiple centres and the presence of neurodegenerative pathology. We also briefly discuss some aspects of the statistical modelling approaches to adjust for TIV. [Display omitted] •288 T1 MRI from multiple scanners were manually segmented for intracranial volume.•We compare SPM12 with the current methods of estimating intracranial volume.•SPM12 shows a very high correlation with manual measures and little bias.•Newer automated volume measures are more accurate controls for head size variation.

Karl Friston began the SPM project around 1991. The rest is history

BackgroundValidating neuroimaging biomarkers that linearly track clinical progression over the lifetime of a HD patient is essential for clinical trials to test drug efficacy and ultimately develop a cure. Different image processing techniques can introduce variability and standardisation is required for cross-study comparison.AimThis study aims to investigate image analysis across three large observational datasets, TRACK-HD, TrackOn-HD and HD-YAS, in order to standardise a processing pipeline for grey and white matter segmentation. In this way, the progression of HD pathology across the entire lifespan can be investigated.MethodsNeuroimaging data from 497 participants from the TRACK-HD, TrackOn-HD and HD-YAS datasets were combined. Original processing with SPM5, SPM8 and standardised processing using the CAT12 tool in SPM12 were compared. Grey and white matter volumes were plotted to observe the development of atrophy in HD. Statistical parametric maps correlating cognitive and motor outcomes with regional atrophy were also assessed.ResultsComparison of SPM5 and SPM8 with SPM12 standardised brain segmentations showed significant differences. The CAT12 pre-processing tool was validated as an accurate method for standardised brain segmentation across both data sets. In the premanifest cohort, caudate volume was the earliest biomarker detected, followed by grey and white matter volumes. Examination of the cognitive tests highlighted a need for more sensitive measures for early premanifest individuals.ConclusionsWe demonstrate a systematic difference between different SPM software versions, which was removed when the CAT12 tool was used. This emphasises the need for standardisation of image analysis processing when combining multiple datasets.

Formation of specialized pro-resolving lipid mediators (SPMs) such as lipoxins or resolvins usually involves arachidonic acid 5-lipoxygenase (5-LO, ALOX5) and different types of arachidonic acid 12- and 15-lipoxygenating paralogues (15-LO1, ALOX15; 15-LO2, ALOX15B; 12-LO, ALOX12). Typically, SPMs are thought to be formed via consecutive steps of oxidation of polyenoic fatty acids such as arachidonic acid, eicosapentaenoic acid or docosahexaenoic acid. One hallmark of SPM formation is that reported levels of these lipid mediators are much lower than typical pro-inflammatory mediators including the monohydroxylated fatty acid derivatives (e.g., 5-HETE), leukotrienes or certain cyclooxygenase-derived prostaglandins. Thus, reliable detection and quantification of these metabolites is challenging. This paper is aimed at critically evaluating i) the proposed biosynthetic pathways of SPM formation, ii) the current knowledge on SPM receptors and their signaling cascades and iii) the analytical methods used to quantify these pro-resolving mediators in the context of their instability and their low concentrations. Based on current literature it can be concluded that i) there is at most, a low biosynthetic capacity for SPMs in human leukocytes. ii) The identity and the signaling of the proposed G-protein-coupled SPM receptors have not been supported by studies in knock-out mice and remain to be validated. iii) In humans, SPM levels were neither related to dietary supplementation with their ω-3 polyunsaturated fatty acid precursors nor were they formed during the resolution phase of an evoked inflammatory response. iv) The reported low SPM levels cannot be reliably quantified by means of the most commonly reported methodology. Overall, these questions regarding formation, signaling and occurrence of SPMs challenge their role as endogenous mediators of the resolution of inflammation.

Clearance of multiple rounds of apoptotic cells (ACs) through continual efferocytosis is critical in the maintenance of organ function, the resolution of acute inflammation, and tissue repair. To date, little is known about the nature of mechanisms and factors that govern this fundamental process. Herein, the authors reported that breakdown of ACs leads to upregulation of 12‐lipoxygenase in macrophages. This enzyme converts docosahexaenoic acid to maresin conjugates in tissue regeneration (MCTRs). The levels of these autacoids are elevated at sites of high apoptotic burden in vivo and in efferocytosing macrophages in vitro. Abrogation of MCTR production using genetic approaches limits the ability of macrophages to perform continual efferocytosis both in vivo and in vitro, an effect that is rescued by add‐back of MCTRs. Mechanistically, MCTR‐mediated priming of macrophages for continual efferocytosis is dependent on alterations in Rac1 signalling and glycolytic metabolism. Inhibition of Rac1 abolishes the ability of MCTRs to increase glucose uptake and efferocytosis in vitro, whereas inhibition of glycolysis limits the MCTR‐mediated increases in efferocytosis and tissue repair. Together, these findings demonstrate that upregulation of MCTRs by efferocytosing macrophages plays a central role in the regulation of continual efferocytosis via the autocrine and paracrine modulation of metabolic pathways. Apoptotic cell uptake by macrophages triggers 12‐lipoxygenase induction and concomitant maresin conjugates in tissue regeneration production via toll‐like receptor 9 and Aryl hydrocarbon receptor signaling. In turn, MCTRs prime macrophages for continual efferocytosis in an autocrine and paracrine manner that is dependent on Rac1 signaling and glycolysis.

We discuss the exciting prospects for a step change in our ability to map and modify matter at the atomic/molecular level by embedding machine learning algorithms in scanning probe microscopy (with a particular focus on scanning tunnelling microscopy, STM). This nano-AI hybrid approach has the far-reaching potential to realise a technology capable of the automated analysis, actuation, and assembly of matter with a precision down to the single chemical bond limit.