Bruton's tyrosine kinase (Btk) is a therapeutic target for rheumatoid arthritis, but the cellular and molecular mechanisms by which Btk mediates inflammation are poorly understood. Here we describe the discovery of CGI1746, a small-molecule Btk inhibitor chemotype with a new binding mode that stabilizes an inactive nonphosphorylated enzyme conformation. CGI1746 has exquisite selectivity for Btk and inhibits both auto- and transphosphorylation steps necessary for enzyme activation. Using CGI1746, we demonstrate that Btk regulates inflammatory arthritis by two distinct mechanisms. CGI1746 blocks B cell receptor-dependent B cell proliferation and in prophylactic regimens reduces autoantibody levels in collagen-induced arthritis. In macrophages, Btk inhibition abolishes FcγRIII-induced TNFα, IL-1β and IL-6 production. Accordingly, in myeloid- and FcγR-dependent autoantibody-induced arthritis, CGI1746 decreases cytokine levels within joints and ameliorates disease. These results provide new understanding of the function of Btk in both B cell- or myeloid cell-driven disease processes and provide a compelling rationale for targeting Btk in rheumatoid arthritis.
Diastolic dysfunction is the inability of the left ventricle to supply sufficient stroke volumes under normal physiological conditions and is often accompanied by stiffening of the left-ventricular myocardium. A noninvasive technique capable of quantifying viscoelasticity of the myocardium would be beneficial in clinical settings. Our group has been investigating the use of Shearwave Dispersion Ultrasound Vibrometry (SDUV), a noninvasive ultrasound based method for quantifying viscoelasticity of soft tissues. The primary motive of this study is the design and testing of viscoelastic materials suitable for validation of the Lamb wave Dispersion Ultrasound Vibrometry (LDUV), an SDUV-based technique for measuring viscoelasticity of tissues with plate-like geometry. We report the results of quantifying viscoelasticity of urethane rubber and gelatin samples using LDUV and an embedded sphere method. The LDUV method was used to excite antisymmetric Lamb waves and measure the dispersion in urethane rubber and gelatin plates. An antisymmetric Lamb wave model was fitted to the wave speed dispersion data to estimate elasticity and viscosity of the materials. A finite element model of a viscoelastic plate submerged in water was used to study the appropriateness of the Lamb wave dispersion equations. An embedded sphere method was used as an independent measurement of the viscoelasticity of the urethane rubber and gelatin. The FEM dispersion data were in excellent agreement with the theoretical predictions. Viscoelasticity of the urethane rubber and gelatin obtained using the LDUV and embedded sphere methods agreed within one standard deviation. LDUV studies on excised porcine myocardium sample were performed to investigate the feasibility of the approach in preparation for open-chest in vivo studies. The results suggest that the LDUV technique can be used to quantify mechanical properties of soft tissues with a plate-like geometry.
Spleen tyrosine kinase (Syk) is an attractive drug target in autoimmune, inflammatory, and oncology disease indications. The most advanced Syk inhibitor, R406, 1 (or its prodrug form fostamatinib, 2), has shown efficacy in multiple therapeutic indications, but its clinical progress has been hampered by dose-limiting adverse effects that have been attributed, at least in part, to the off-target activities of 1. It is expected that a more selective Syk inhibitor would provide a greater therapeutic window. Herein we report the discovery and optimization of a novel series of imidazo[1,2-a]pyrazine Syk inhibitors. This work culminated in the identification of GS-9973, 68, a highly selective and orally efficacious Syk inhibitor which is currently undergoing clinical evaluation for autoimmune and oncology indications.
Background: Repurposed medicines may have a role against the SARS-CoV-2 virus. The antiparasitic ivermectin, with antiviral and anti-inflammatory properties, has now been tested in numerous clinical trials. Areas of uncertainty: We assessed the efficacy of ivermectin treatment in reducing mortality, in secondary outcomes, and in chemoprophylaxis, among people with, or at high risk of, COVID-19 infection. Data sources: We searched bibliographic databases up to April 25, 2021. Two review authors sifted for studies, extracted data, and assessed risk of bias. Meta-analyses were conducted and certainty of the evidence was assessed using the GRADE approach and additionally in trial sequential analyses for mortality. Twenty-four randomized controlled trials involving 3406 participants met review inclusion. Therapeutic Advances: Meta-analysis of 15 trials found that ivermectin reduced risk of death compared with no ivermectin (average risk ratio 0.38, 95% confidence interval 0.19–0.73; n = 2438; I 2 = 49%; moderate-certainty evidence). This result was confirmed in a trial sequential analysis using the same DerSimonian–Laird method that underpinned the unadjusted analysis. This was also robust against a trial sequential analysis using the Biggerstaff–Tweedie method. Low-certainty evidence found that ivermectin prophylaxis reduced COVID-19 infection by an average 86% (95% confidence interval 79%–91%). Secondary outcomes provided less certain evidence. Low-certainty evidence suggested that there may be no benefit with ivermectin for “need for mechanical ventilation,” whereas effect estimates for “improvement” and “deterioration” clearly favored ivermectin use. Severe adverse events were rare among treatment trials and evidence of no difference was assessed as low certainty. Evidence on other secondary outcomes was very low certainty. Conclusions: Moderate-certainty evidence finds that large reductions in COVID-19 deaths are possible using ivermectin. Using ivermectin early in the clinical course may reduce numbers progressing to severe disease. The apparent safety and low cost suggest that ivermectin is likely to have a significant impact on the SARS-CoV-2 pandemic globally.
Figure 1: In maximal Poisson-disk sampling disks cover the domain and half-radius disks do not overlap. In 2d we generate 1 million points in 12 seconds (serial) and 1 second (GPU). The software is practical in up to 5d (serial) and 3d (GPU). AbstractWe provide a simple algorithm and data structures for d-dimensional unbiased maximal Poisson-disk sampling. We use an order of magnitude less memory and time than the alternatives. Our results become more favorable as the dimension increases. This allows us to produce bigger samplings. Domains may be non-convex with holes. The generated point cloud is maximal up to round-off error. The serial algorithm is provably bias-free. For an output sampling of size n in fixed dimension d, we use a linear memory budget and empirical Θ(n) runtime. No known methods scale well with dimension, due to the "curse of dimensionality." The serial algorithm is practical in dimensions up to 5, and has been demonstrated in 6d. We have efficient GPU implementations in 2d and 3d. The algorithm proceeds through a finite sequence of uniform grids. The grids guide the dart throwing and track the remaining disk-free area. The top-level grid provides an efficient way to test if a candidate dart is disk-free. Our uniform grids are like quadtrees, except we delay splits and refine all leaves at once. Since the quadtree is flat it can be represented using very little memory: we just need the indices of the active leaves and a global level. Also it is very simple to sample from leaves with uniform probability.
The synthesis of 18 N-alpha-FMOC-amino acid glycosides for solid-phase glycopeptide assembly is reported. The glycosides were synthesized either from the corresponding O'Donnell Schiff bases or from N-alpha-FMOC-amino protected serine or threonine and the appropriate glycosyl bromide using Hanessian's modification of the Koenigs-Knorr reaction. Reaction rates of D-glycosyl bromides (e.g., acetobromoglucose) with the L- and D-forms of serine and threonine are distinctly different and can be rationalized in terms of the steric interactions within the two types of diastereomeric transition states for the D/L and D/D reactant pairs. The N-alpha-FMOC-protected glycosides [monosaccharides Xyl, Glc, Gal, Man, GlcNAc, and GalNAc; disaccharides Gal-beta(1-4)-Glc (lactose), Glc-beta(1-4)-Glc (cellobiose), and Gal-alpha(1-6)-Glc (melibiose)] were incorporated into 22 enkephalin glycopeptide analogues. These peptide opiates bearing the pharmacophore H-Tyr-c[DCys-Gly-Phe-DCys]- were designed to probe the significance of the glycoside moiety and the carbohydrate-peptide linkage region in blood-brain barrier (BBB) transport, opiate receptor binding, and analgesia.
Endogenous peptides (e.g. enkephalins) control many aspects of brain function, cognition, and perception. The use of these neuroactive peptides in diverse studies has led to an increased understanding of brain function. Unfortunately, the use of brain-derived peptides as pharmaceutical agents to alter brain chemistry in vivo has lagged because peptides do not readily penetrate the blood-brain barrier. Attachment of simple sugars to enkephalins increases their penetration of the blood-brain barrier and allows the resulting glycopeptide analogues to function effectively as drugs. The delta-selective glycosylated Leu-enkephalin amide 2, H(2)N-Tyr-D-Thr-Gly-Phe-Leu-Ser(beta-D-Glc)-CONH(2), produces analgesic effects similar to morphine, even when administered peripherally, yet possesses reduced dependence liability as indicated by naloxone-precipitated withdrawal studies. Similar glycopeptide-based pharmaceuticals hold forth the promise of pain relief with improved side-effect profiles over currently available opioid analgesics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.