Benign chondroid syringoma of the orbit: a rare cause of exophtalmos

Chondroid syringoma (CS) of the orbit is an extremely rare benign neoplasm. To the best of our knowledege, this is the second case reported in the english litérature

Physical activity to improve cognition in older adults: can physical activity programs enriched with cognitive challenges enhance the effects? A systematic review and meta-analysis

: EPHPP quality rating scores (DOCX 38 kb

Stroke Rehabilitation Reaches a Threshold

Motor training with the upper limb affected by stroke partially reverses the loss of cortical representation after lesion and has been proposed to increase spontaneous arm use. Moreover, repeated attempts to use the affected hand in daily activities create a form of practice that can potentially lead to further improvement in motor performance. We thus hypothesized that if motor retraining after stroke increases spontaneous arm use sufficiently, then the patient will enter a virtuous circle in which spontaneous arm use and motor performance reinforce each other. In contrast, if the dose of therapy is not sufficient to bring spontaneous use above threshold, then performance will not increase and the patient will further develop compensatory strategies with the less affected hand. To refine this hypothesis, we developed a computational model of bilateral hand use in arm reaching to study the interactions between adaptive decision making and motor relearning after motor cortex lesion. The model contains a left and a right motor cortex, each controlling the opposite arm, and a single action choice module. The action choice module learns, via reinforcement learning, the value of using each arm for reaching in specific directions. Each motor cortex uses a neural population code to specify the initial direction along which the contralateral hand moves towards a target. The motor cortex learns to minimize directional errors and to maximize neuronal activity for each movement. The derived learning rule accounts for the reversal of the loss of cortical representation after rehabilitation and the increase of this loss after stroke with insufficient rehabilitation. Further, our model exhibits nonlinear and bistable behavior: if natural recovery, motor training, or both, brings performance above a certain threshold, then training can be stopped, as the repeated spontaneous arm use provides a form of motor learning that further bootstraps performance and spontaneous use. Below this threshold, motor training is “in vain”: there is little spontaneous arm use after training, the model exhibits learned nonuse, and compensatory movements with the less affected hand are reinforced. By exploring the nonlinear dynamics of stroke recovery using a biologically plausible neural model that accounts for reversal of the loss of motor cortex representation following rehabilitation or the lack thereof, respectively, we can explain previously hard to reconcile data on spontaneous arm use in stroke recovery. Further, our threshold prediction could be tested with an adaptive train–wait–train paradigm: if spontaneous arm use has increased in the “wait” period, then the threshold has been reached, and rehabilitation can be stopped. If spontaneous arm use is still low or has decreased, then another bout of rehabilitation is to be provided

An efficient method for thickness prediction in multi-pass incremental sheet forming

Incremental sheet forming (ISF) is a highly versatile and flexible process for rapid manufacturing of complex sheet metal parts. In the ISF process, efficient and accurate prediction of part thickness variation is still a challenging task, which is especially true for the multi-pass ISF process. The Sine law equation and the finite element method (FEM) are the two commonly used conventional prediction methods. However, these approaches are either with limited accuracy or very time consuming. For the multi-pass ISF process, the thickness prediction is even more challenging since two or more forming steps are involved. Focusing on the thickness prediction of multi-stage ISF process, this work proposes a thickness prediction model based on the geometrical calculation of intermediate shapes of the formed part and backward tracing of nodal points of the forming tool. By developing this method, the thickness distribution can be calculated through the predicted nodal displacement in the ISF process. To verify the proposed model, four different geometrical shapes, i.e., conic, parabolic conic, non-axisymmetric, and hemispherical parts, are physically formed by using a NC ISF machine. The geometric shapes and the detailed thickness distributions of the formed parts are carefully measured and compared with the prediction model developed. Good agreements between the analytical predictions, and the experimental results are obtained. This indicates the effectiveness and robustness of the developed thickness prediction approach

Non-Steroidal Anti-Inflammatory Drugs and Cognitive Function: Are Prostaglandins at the Heart of Cognitive Impairment in Dementia and Delirium ?

Studies of non-steroidal anti-inflammatory drugs (NSAIDs) in rheumatoid arthritis imply that inflammation is important in the development of Alzheimer’s disease (AD). However, these drugs have not alleviated the symptoms of AD in those who have already developed dementia. This suggests that the primary mediator targeted by these drugs, PGE2, is not actively suppressing memory function in AD. Amyloid-β oligomers appear to be important for the mild cognitive changes seen in AD transgenic mice, yet amyloid immunotherapy has also proven unsuccessful in clinical trials. Collectively, these findings indicate that NSAIDs may target a prodromal process in mice that has already passed in those diagnosed with AD, and that synaptic and neuronal loss are key determinants of cognitive dysfunction in AD. While the role of inflammation has not yet become clear, inflammatory processes definitely have a negative impact on cognitive function during episodes of delirium during dementia. Delirium is an acute and profound impairment of cognitive function frequently occurring in aged and demented patients exposed to systemic inflammatory insults, which is now recognised to contribute to long-term cognitive decline. Recent work in animal models is beginning to shed light on the interactions between systemic inflammation and CNS pathology in these acute exacerbations of dementia. This review will assess the role of prostaglandin synthesis in the memory impairments observed in dementia and delirium and will examine the relative contribution of amyloid, synaptic and neuronal loss. We will also discuss how understanding the role of inflammatory mediators in delirious episodes will have major implications for ameliorating the rate of decline in the demented population

Toll-like receptor 4 signaling in liver injury and hepatic fibrogenesis

Toll-like receptors (TLRs) are a family of transmembrane pattern recognition receptors (PRR) that play a key role in innate and adaptive immunity by recognizing structural components unique to bacteria, fungi and viruses. TLR4 is the most studied of the TLRs, and its primary exogenous ligand is lipopolysaccharide, a component of Gram-negative bacterial walls. In the absence of exogenous microbes, endogenous ligands including damage-associated molecular pattern molecules from damaged matrix and injured cells can also activate TLR4 signaling. In humans, single nucleotide polymorphisms of the TLR4 gene have an effect on its signal transduction and on associated risks of specific diseases, including cirrhosis. In liver, TLR4 is expressed by all parenchymal and non-parenchymal cell types, and contributes to tissue damage caused by a variety of etiologies. Intact TLR4 signaling was identified in hepatic stellate cells (HSCs), the major fibrogenic cell type in injured liver, and mediates key responses including an inflammatory phenotype, fibrogenesis and anti-apoptotic properties. Further clarification of the function and endogenous ligands of TLR4 signaling in HSCs and other liver cells could uncover novel mechanisms of fibrogenesis and facilitate the development of therapeutic strategies

Search for gravitational waves associated with gamma-ray bursts detected by Fermi and Swift during the LIGO–Virgo run O3b

We search for gravitational-wave signals associated with gamma-ray bursts (GRBs) detected by the Fermi and Swift satellites during the second half of the third observing run of Advanced LIGO and Advanced Virgo (2019 November 1 15:00 UTC–2020 March 27 17:00 UTC). We conduct two independent searches: a generic gravitational-wave transients search to analyze 86 GRBs and an analysis to target binary mergers with at least one neutron star as short GRB progenitors for 17 events. We find no significant evidence for gravitational-wave signals associated with any of these GRBs. A weighted binomial test of the combined results finds no evidence for subthreshold gravitational-wave signals associated with this GRB ensemble either. We use several source types and signal morphologies during the searches, resulting in lower bounds on the estimated distance to each GRB. Finally, we constrain the population of low-luminosity short GRBs using results from the first to the third observing runs of Advanced LIGO and Advanced Virgo. The resulting population is in accordance with the local binary neutron star merger rate