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Pirates
Provides information on pirates, describing their daily living practices and culture, and includes a timeline, maps, and a quiz.
Book
Long-term safety of secukinumab in patients with moderate-to-severe plaque psoriasis, psoriatic arthritis, and ankylosing spondylitis: integrated pooled clinical trial and post-marketing surveillance data
Background
Secukinumab, a fully human immunoglobulin G1-kappa monoclonal antibody that directly inhibits interleukin (IL)-17A, has been shown to have robust efficacy in the treatment of moderate-to-severe psoriasis (PsO), psoriatic arthritis (PsA), and ankylosing spondylitis (AS) demonstrating a rapid onset of action and sustained long-term clinical responses with a consistently favorable safety profile in multiple Phase 2 and 3 trials. Here, we report longer-term pooled safety and tolerability data for secukinumab across three indications (up to 5 years of treatment in PsO and PsA; up to 4 years in AS).
Methods
The integrated clinical trial safety dataset included data pooled from 21 randomized controlled clinical trials of secukinumab 300 or 150 or 75 mg in PsO (14 Phase 3 trials and 1 Phase 4 trial), PsA (3 Phase 3 trials), and AS (3 Phase 3 trials), along with post-marketing safety surveillance data with a cut-off date of June 25, 2017. Adverse events (AEs) were reported as exposure-adjusted incident rates (EAIRs) per 100 patient-years. Analyses included all patients who received ≥ 1 dose of secukinumab.
Results
A total of 5181, 1380, and 794 patients from PsO, PsA, and AS clinical trials representing secukinumab exposures of 10,416.9, 3866.9, and 1943.1 patient-years, respectively, and post-marketing data from patients with a cumulative exposure to secukinumab of ~ 96,054 patient-years were included in the analysis. The most frequent AE was upper respiratory tract infection. EAIRs across PsO, PsA, and AS indications were generally low for serious infections (1.4, 1.9, and 1.2, respectively),
Candida
infections (2.2, 1.5, and 0.7, respectively), inflammatory bowel disease (0.01, 0.05, and 0.1, respectively), and major adverse cardiac events (0.3, 0.4, and 0.6, respectively). No cases of tuberculosis reactivation were reported. The incidence of treatment-emergent anti-drug antibodies was low with secukinumab across all studies, with no discernible loss of efficacy, unexpected alterations in pharmacokinetics, or association with immunogenicity-related AEs.
Conclusions
Secukinumab demonstrated a favorable safety profile over long-term treatment in patients with PsO, PsA, and AS. This comprehensive assessment demonstrated that the safety profile of secukinumab was consistent with previous reports in patients with PsO, PsA, and AS, supporting its long-term use in these chronic conditions.
Journal Article
Neural network of cognitive emotion regulation — An ALE meta-analysis and MACM analysis
Cognitive regulation of emotions is a fundamental prerequisite for intact social functioning which impacts on both well being and psychopathology. The neural underpinnings of this process have been studied intensively in recent years, without, however, a general consensus. We here quantitatively summarize the published literature on cognitive emotion regulation using activation likelihood estimation in fMRI and PET (23 studies/479 subjects). In addition, we assessed the particular functional contribution of identified regions and their interactions using quantitative functional inference and meta-analytic connectivity modeling, respectively. In doing so, we developed a model for the core brain network involved in emotion regulation of emotional reactivity. According to this, the superior temporal gyrus, angular gyrus and (pre) supplementary motor area should be involved in execution of regulation initiated by frontal areas. The dorsolateral prefrontal cortex may be related to regulation of cognitive processes such as attention, while the ventrolateral prefrontal cortex may not necessarily reflect the regulatory process per se, but signals salience and therefore the need to regulate. We also identified a cluster in the anterior middle cingulate cortex as a region, which is anatomically and functionally in an ideal position to influence behavior and subcortical structures related to affect generation. Hence this area may play a central, integrative role in emotion regulation. By focusing on regions commonly active across multiple studies, this proposed model should provide important a priori information for the assessment of dysregulated emotion regulation in psychiatric disorders.
•We quantitatively summarize the literature on emotion regulation (ER) using ALE.•Using MACM and quantitative functional inference we develop a neural model of ER.•DLPFC is related to higher order “cold” regulatory processes.•VLPFC evaluates salience and indicates need to regulate.•STG, angular gyrus and SMA are associated to execution of regulation.
Journal Article
Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation
Given the increasing number of neuroimaging publications, the automated knowledge extraction on brain-behavior associations by quantitative meta-analyses has become a highly important and rapidly growing field of research. Among several methods to perform coordinate-based neuroimaging meta-analyses, Activation Likelihood Estimation (ALE) has been widely adopted. In this paper, we addressed two pressing questions related to ALE meta-analysis: i) Which thresholding method is most appropriate to perform statistical inference? ii) Which sample size, i.e., number of experiments, is needed to perform robust meta-analyses? We provided quantitative answers to these questions by simulating more than 120,000 meta-analysis datasets using empirical parameters (i.e., number of subjects, number of reported foci, distribution of activation foci) derived from the BrainMap database. This allowed to characterize the behavior of ALE analyses, to derive first power estimates for neuroimaging meta-analyses, and to thus formulate recommendations for future ALE studies. We could show as a first consequence that cluster-level family-wise error (FWE) correction represents the most appropriate method for statistical inference, while voxel-level FWE correction is valid but more conservative. In contrast, uncorrected inference and false-discovery rate correction should be avoided. As a second consequence, researchers should aim to include at least 20 experiments into an ALE meta-analysis to achieve sufficient power for moderate effects. We would like to note, though, that these calculations and recommendations are specific to ALE and may not be extrapolated to other approaches for (neuroimaging) meta-analysis.
Journal Article
The effect of lower inter-limb asymmetries on athletic performance: A systematic review and meta-analysis
Inter-limb asymmetry refers to an imbalance in performance between the left and right limbs. Discrepancies throughout asymmetry research does not allow practitioners to confidently understand the effect of inter-limb asymmetries on athletic performance. Therefore, this review summarized the current literature using a meta-analytic approach, conforming to the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines to identify the association between inter-limb asymmetry and athletic performance. A literature search using PubMed, Web of Science and SPORTDiscus databases yielded 11-studies assessing the effect of inter-limb asymmetries, measured via unilateral jump performance, on bilateral jump, change of direction (COD) and sprint performance in adult sports players. The quality of evidence was assessed via a modified Downs and Black checklist and in compliance with the Grading of Recommendations Assessment Development and Evaluation. Correlation coefficients were transformed via Fishers z ( Z r ), meta-analysed and then re-converted to correlation coefficients. Egger’s regression presented no significant risk of bias. Vertical jump performance was not significantly affected by asymmetry ( Z r = 0.053, r = 0.05; P = 0.874), whereas COD and sprint both presented significant weak associations (COD, Z r = 0.243, r = 0.24; Sprint, Z r = 0.203, r = 0.2; P < 0.01). The results demonstrate that inter-limb asymmetries seem to present a negative impact to COD and sprint performance but not vertical jump performance. Practitioners should consider implementing monitoring strategies to identify, monitor and possibly address inter-limb asymmetries, specifically for performance tests underpinned by unilateral movements such as COD and sprint performance.
Journal Article
Deep neural network heatmaps capture Alzheimer’s disease patterns reported in a large meta-analysis of neuroimaging studies
•We assessed the ability of deep networks heatmaps to capture AD effects on the brain.•SVMs, CNNs and ResNets were trained to classify 502 ADNI T1 MRIs.•GGC, integrated gradient and LRP used to produce heatmaps for the best classifiers.•Heatmaps were compared with a meta-analysis of 77 VBM studies and SVM activations.•Integrated gradient heatmaps produced the best overlap with the meta-analysis.
Deep neural networks currently provide the most advanced and accurate machine learning models to distinguish between structural MRI scans of subjects with Alzheimer’s disease and healthy controls. Unfortunately, the subtle brain alterations captured by these models are difficult to interpret because of the complexity of these multi-layer and non-linear models. Several heatmap methods have been proposed to address this issue and analyze the imaging patterns extracted from the deep neural networks, but no quantitative comparison between these methods has been carried out so far. In this work, we explore these questions by deriving heatmaps from Convolutional Neural Networks (CNN) trained using T1 MRI scans of the ADNI data set and by comparing these heatmaps with brain maps corresponding to Support Vector Machine (SVM) activation patterns. Three prominent heatmap methods are studied: Layer-wise Relevance Propagation (LRP), Integrated Gradients (IG), and Guided Grad-CAM (GGC). Contrary to prior studies where the quality of heatmaps was visually or qualitatively assessed, we obtained precise quantitative measures by computing overlap with a ground-truth map from a large meta-analysis that combined 77 voxel-based morphometry (VBM) studies independently from ADNI. Our results indicate that all three heatmap methods were able to capture brain regions covering the meta-analysis map and achieved better results than SVM activation patterns. Among them, IG produced the heatmaps with the best overlap with the independent meta-analysis.
Journal Article
Correspondence of the brain's functional architecture during activation and rest
Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is \"at rest.\" In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically \"active\" even when at \"rest.\"
Journal Article
Hemodynamic and metabolic correspondence of resting-state voxel-based physiological metrics in healthy adults
•ALFF spatially correlates significantly only with BV.•Conditioned by BV, ALFF contains no other physiological information.•fALFF and ReHo spatially correlate most strongly with MRGlu, but also with MRO2,BF and BV.•Conditioned by MRGlu, fALFF and ReHo contain little physiological information.
Voxel-based physiological (VBP) variables derived from blood oxygen level dependent (BOLD) fMRI time-course variations include: amplitude of low frequency fluctuations (ALFF), fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity (ReHo). Although these BOLD-derived variables can detect between-group (e.g. disease vs control) spatial pattern differences, physiological interpretations are not well established. The primary objective of this study was to quantify spatial correspondences between BOLD VBP variables and PET measurements of cerebral metabolic rate and hemodynamics, being well-validated physiological standards. To this end, quantitative, whole-brain PET images of metabolic rate of glucose (MRGlu; 18FDG) and oxygen (MRO2; 15OO), blood flow (BF; H215O) and blood volume (BV; C15O) were obtained in 16 healthy controls. In the same subjects, BOLD time-courses were obtained for computation of ALFF, fALFF and ReHo images. PET variables were compared pair-wise with BOLD variables. In group-averaged, across-region analyses, ALFF corresponded significantly only with BV (R = 0.64; p < 0.0001). fALFF corresponded most strongly with MRGlu (R = 0.79; p < 0.0001), but also significantly (p < 0.0001) with MRO2 (R = 0.68), BF (R = 0.68) and BV (R=0.68). ReHo performed similarly to fALFF, with significant strong correspondence (p < 0.0001) with MRGlu (R = 0.78), MRO2 (R = 0.54), and, but less strongly with BF (R = 0.50) and BV (R=0.50). Mutual information analyses further clarified these physiological interpretations. When conditioned by BV, ALFF retained no significant MRGlu, MRO2 or BF information. When conditioned by MRGlu, fALFF and ReHo retained no significant MRO2, BF or BV information. Of concern, however, the strength of PET-BOLD correspondences varied markedly by brain region, which calls for future investigation on physiological interpretations at a regional and per-subject basis.
Journal Article
Ionic liquids behave as dilute electrolyte solutions
We combine direct surface force measurements with thermodynamic arguments to demonstrate that pure ionic liquids are expected to behave as dilute weak electrolyte solutions, with typical effective dissociated ion concentrations of less than 0.1% at room temperature. We performed equilibrium force–distance measurements across the common ionic liquid 1-butyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide ([C ₄mim][NTf ₂]) using a surface forces apparatus with in situ electrochemical control and quantitatively modeled these measurements using the van der Waals and electrostatic double-layer forces of the Derjaguin–Landau–Verwey–Overbeek theory with an additive repulsive steric (entropic) ion–surface binding force. Our results indicate that ionic liquids screen charged surfaces through the formation of both bound (Stern) and diffuse electric double layers, where the diffuse double layer is comprised of effectively dissociated ionic liquid ions. Additionally, we used the energetics of thermally dissociating ions in a dielectric medium to quantitatively predict the equilibrium for the effective dissociation reaction of [C ₄mim][NTf ₂] ions, in excellent agreement with the measured Debye length. Our results clearly demonstrate that, outside of the bound double layer, most of the ions in [C ₄mim][NTf ₂] are not effectively dissociated and thus do not contribute to electrostatic screening. We also provide a general, molecular-scale framework for designing ionic liquids with significantly increased dissociated charge densities via judiciously balancing ion pair interactions with bulk dielectric properties. Our results clear up several inconsistencies that have hampered scientific progress in this important area and guide the rational design of unique, high–free-ion density ionic liquids and ionic liquid blends.
Journal Article