Glatiramer acetate reduces the risk for experimental cerebral malaria: a pilot study

<p>Abstract</p> <p>Background</p> <p>Cerebral malaria (CM) is associated with high mortality and morbidity caused by a high rate of transient or persistent neurological sequelae. Studies on immunomodulatory and neuroprotective drugs as ancillary treatment in murine CM indicate promising potential. The current study was conducted to evaluate the efficacy of glatiramer acetate (GA), an immunomodulatory drug approved for the treatment of relapsing remitting multiple sclerosis, in preventing the death of C57Bl/6J mice infected with <it>Plasmodium berghei </it>ANKA.</p> <p>Methods and Results</p> <p>GA treatment led to a statistically significant lower risk for developing CM (57.7% versus 84.6%) in treated animals. The drug had no effect on the course of parasitaemia. The mechanism of action seems to be an immunomodulatory effect since lower IFN-gamma levels were observed in treated animals in the early course of the disease (day 4 post-infection) which also led to a lower number of brain sequestered leukocytes in treated animals. No direct neuro-protective effect such as an inhibition of apoptosis or reduction of micro-bleedings in the brain was found.</p> <p>Conclusion</p> <p>These findings support the important role of the host immune response in the pathophysiology of murine CM and might lead to the development of new adjunctive treatment strategies.</p

Incrementally learning semantic attributes through dialogue interaction

Enabling a robot to properly interact with users plays a key role in the effective deployment of robotic platforms in domestic environments. Robots must be able to rely on interaction to improve their behaviour and adaptively understand their operational world. Semantic mapping is the task of building a representation of the environment, that can be enhanced through interaction with the user. In this task, a proper and effective acquisition of semantic attributes of targeted entities is essential for the task accomplishment itself. In this paper, we focus on the problem of learning dialogue policies to support semantic attribute acquisition, so that the effort required by humans in providing knowledge to the robot through dialogue is minimized. To this end, we design our Dialogue Manager as a multi-objective Markov Decision Process, solving the optimisation problem through Reinforcement Learning. The Dialogue Manager interfaces with an online incremental visual classifier, based on a Load-Balancing Self-Organizing Incremental Neural Network (LB-SOINN). Experiments in a simulated scenario show the effectiveness of the proposed solution, suggesting that perceptual information can be properly exploited to reduce human tutoring cost. Moreover, a dialogue policy trained on a small amount of data generalises well to larger datasets, and so the proposed online scheme, as well as the real-time nature of the processing, are suited for an extensive deployment in real scenarios. To this end, this paper provides a demonstration of the complete system on a real robot

Heat exposure and perinatal mortality: A time- stratied, case-crossover study from 16 hospitals in Benin, Malawi, Tanzania and Uganda

Extreme heat events affect both pregnant women and their infants. We applied a time-stratied case- crossover design including 124,819 singleton births in a prospective observational study in 16 hospitals in Benin, Malawi, Tanzania, and Uganda to investigate the association between extreme heat and timing of perinatal death. We observed weak associations between heat exposure and perinatal mortality with an odds ratio of 1.22 (95%CI 0.85-1.73) for stillbirths; 1.10 (95%CI 0.51-2.34) for antepartum and 1.54 (95%CI 0.63-3.73) for intrapartum stillbirths; and 1.17 (95%CI 0.84-2.61) for perinatal deaths with an increase from 75th to 99th percentile in mean temperature one week (lag 0-6 days) before childbirth. The cumulative exposure- response curve suggested the steepest slope for heat was in intrapartum stillbirths, and stronger associations during the hottest seasons. We conclude that higher temperatures may have short-term effects on mortality risks, particularly for intrapartum stillbirths, raising the importance of improved intrapartum care

X-Ray Computed Tomography for Dimensional Metrology

X-ray computed tomography (CT) has emerged over the last years as an innovative dimensional measuring technique and has been increasingly applied in industry. This chapter describes the state of the art, the main technical characteristics, and examples of applications of CT in industrial dimensional metrology. Although still in its youth, metrological CT offers unique solutions and provides several advantages in comparison to other coordinate measuring systems such as tactile coordinate measuring machines. In particular, CT systems allow reconstructing holistic three-dimensional models of the scanned workpieces, which are then used to obtain nondestructive and noncontact measurements of outer as well as inner features. However, important drawbacks still limit a wider acceptance of CT in industrial metrology. One of the most critical aspects is the establishment of metrological traceability, which is often challenging due to many and complex error sources that affect CT measurements and complicate the evaluation of metrological performances and of task-specific uncertainties

Doping Method Determines Para- or Superparamagnetic Properties of Photostable and Surface-Modifiable Quantum Dots for Multimodal Bioimaging

Semiconductor quantum dots (QDs) are widely used for optical applications and bioimaging. In comparison to organic dyes used for fluorescent labeling, QDs exhibit very high photostability and can be further surface modified. Equipping QDs with magnetic properties (mQDs) makes it possible to combine fluorescence and magnetic resonance imaging analyses. For this purpose, we have prepared water-dispersible and magnetic CdTe/ZnS mQDs, whereby ferrous ions are selectively incorporated in either their cores or their shells. This study aims at understanding the differences in optical, structural, and magnetic properties between these core- and shell-doped mQDs. Field-dependent isothermal magnetic susceptibility measurements show that shell-doped mQDs exhibit paramagnetic and their core-doped equivalents super­paramagnetic behavior near room temperature. Shell doping results in about 1.7 times higher photoluminescence quantum yields and 1.4 times higher doping efficiency than core doping. X-ray diffraction patterns reveal that core doping leads to defects in the lattice and hence to a severe decrease in crystallinity, whereas shell doping has no significant impact on the crystal structure and consequently fewer disadvantages regarding the mQD’s quantum yield. These selective doping approaches, particularly shell doping, allow for the tailored design of paramagnetic QDs having modifiable and biocompatible particle surfaces. The organic ligandsin this study <i>N</i>-acetyl-l-cysteinesufficiently prevent leakage of toxic metal ions, as shown by cytotoxicity assays with HepG2 cells. Confocal laser scanning microscopy shows that mQDs are internalized by these cells and accumulated near their nuclei. This study shows that biocompatible, fluorescent, and paramagnetic QDs are promising photostable labels for multimodal bioimaging