A Novel Neurofilament Light Chain ELISA Validated in Patients with Alzheimer’s Disease,Frontotemporal Dementia,and Subjective Cognitive Decline,and the Evaluation of Candidate Proteins for Immunoassay Calibration

Neurofilament light chain (Nf-L) is a well-known biomarker for axonal damage; however, the corresponding circulating Nf-L analyte in cerebrospinal fluid (CSF) is poorly characterized. We therefore isolated new monoclonal antibodies against synthetic peptides, and these monoclonals were characterized for their specificity on brain-specific intermediate filament proteins. Two highly specific antibodies, ADx206 and ADx209, were analytically validated for CSF applications according to well-established criteria. Interestingly, using three different sources of purified Nf-L proteins, a significant impact on interpolated concentrations was observed. With a lower limit of analytical sensitivity of 100 pg/mL using bovine Nf-L as the calibrator, we were able to quantify the Nf-L analyte in each sample, and these Nf-L concentrations were highly correlated to the Uman diagnostics assay (Spearman rho = 0.97, p < 0.001). In the clinical diagnostic groups, the new Nf-L ELISA could discriminate patients with Alzheimer’s disease (AD, n = 20) from those with frontotemporal lobe dementia (FTD, n = 20) and control samples with subjective cognitive decline (SCD, n = 20). Henceforth, this novel Nf-L ELISA with well-defined specificity and epitopes can be used to enhance our understanding of harmonizing the use of Nf-L as a clinically relevant marker for neurodegeneration in CSF.     

Introduction to the Special Issue on Meta-Learning

Recent advances in meta-learning are providing the foundations to construct meta-learning assistants and task-adaptive learners. The goal of this special issue is to foster an interest in meta-learning by compiling representative work in the field. The contributions to this special issue provide strong insights into the construction of future meta-learning tools. In this introduction we present a common frame of reference to address work in meta-learning through the concept of meta-knowledge. We show how meta-learning can be simply defined as the process of exploiting knowledge about learning that enables us to understand and improve the performance of learning algorithms.     

Chelating Polymers for Targeted Decontamination of Actinides: Application of PEI-MP to Hydroxyapatite-Th(IV)

In case of an incident in the nuclear industry or an act of war or terrorism, the dissemination of plutonium could contaminate the environment and, hence, humans. Human contamination mainly occurs via inhalation and/or wounding (and, less likely, ingestion). In such cases, plutonium, if soluble, reaches circulation, whereas the poorly soluble fraction (such as small colloids) is trapped in alveolar macrophages or remains at the site of wounding. Once in the blood, the plutonium is delivered to the liver and/or to the bone, particularly into its mineral part, mostly composed of hydroxyapatite. Countermeasures against plutonium exist and consist of intravenous injections or inhalation of diethylenetetraminepentaacetate salts. Their effectiveness is, however, mainly confined to the circulating soluble forms of plutonium. Furthermore, the short bioavailability of diethylenetetraminepentaacetate results in its rapid elimination. To overcome these limitations and to provide a complementary approach to this common therapy, we developed polymeric analogs to indirectly target the problematic retention sites. We present herein a first study regarding the decontamination abilities of polyethyleneimine methylcarboxylate (structural diethylenetetraminepentaacetate polymer analog) and polyethyleneimine methylphosphonate (phosphonate polymeric analog) directed against Th(IV), used here as a Pu(IV) surrogate, which was incorporated into hydroxyapatite used as a bone model. Our results suggest that polyethylenimine methylphosphonate could be a good candidate for powerful bone decontamination action.     

Overview of the MPEG Reconfigurable Video Coding Framework

Video coding technology in the last 20 years has evolved producing a variety of different and complex algorithms and coding standards. So far the specification of such standards, and of the algorithms that build them, has been done case by case providing monolithic textual and reference software specifications in different forms and programming languages. However, very little attention has been given to provide a specification formalism that explicitly presents common components between standards, and the incremental modifications of such monolithic standards. The MPEG Reconfigurable Video Coding (RVC) framework is a new ISO standard currently under its final stage of standardization, aiming at providing video codec specifications at the level of library components instead of monolithic algorithms. The new concept is to be able to specify a decoder of an existing standard or a completely new configuration that may better satisfy application-specific constraints by selecting standard components from a library of standard coding algorithms. The possibility of dynamic configuration and reconfiguration of codecs also requires new methodologies and new tools for describing the new bitstream syntaxes and the parsers of such new codecs. The RVC framework is based on the usage of a new actor/ dataflow oriented language called CAL for the specification of the standard library and instantiation of the RVC decoder model. This language has been specifically designed for modeling complex signal processing systems. CAL dataflow models expose the intrinsic concurrency of the algorithms by employing the notions of actor programming and dataflow. The paper gives an overview of the concepts and technologies building the standard RVC framework and the non standard tools supporting the RVC model from the instantiation and simulation of the CAL model to software and/or hardware code synthesis.     

Study on conductivity and redox stability of iron orthovanadate

FeVO₄ was synthesised by conventional solid state technique. Impedance measurements using a silver electrode were unsuccessful due to a solid state reaction between FeVO₄ and Ag, forming α-AgVO₃ and α-Fe₂O₃ at the interface. Impedance measurements, with a platinum electrode, reaffirmed that FeVO₄ exhibits semiconductor behaviour in air. In a reducing atmosphere, 5% H₂/Ar, high electronic conductivity, from 1 S cm⁻¹ at 300 °C to 2 S cm⁻¹ at 700 °C, was observed with an activation energy of 0.13(1) eV. X-ray diffraction, thermogravimetric analysis and differential scanning calorimetry data determined that the change in electronic conductivity was due to the degradation of the material into FeV₂O₄ and α-Fe₂O₃. It is believed that the conduction was due to electron hopping between vanadium d-orbitals. Neither FeVO₄ nor FeV₂O₄ are deemed suitable as anode materials for solid oxide fuel cells, due to redox instability.     

Multiparametric analysis within the proper generalized decomposition framework

Optimization campaigns, which are being launched more and more often, require the execution of many parametric studies which can make the approach very costly in terms of computation time. Here, in order to reduce these computation times, we undertake to develop a multiparametric strategy using the LATIN method along with Proper Generalized Decomposition. This approach is compared to other common strategies, especially those based on POD.