Natalizumab treatment reduces L-selectin (CD62L) in CD4+ T cells

Background: The purpose of this research was to validate the low expression of L-selectin (CD62L) in natalizumab (NTZ)-treated patients. CD62L is involved in rolling and transmigration of leukocyte cells. A correlation between CD62LCD4+ T cells low expression and progressive multifocal leukoencephalopathy (PML) development has been suggested in multiple sclerosis (MS) patients treated with NTZ. Methods: We performed a flow cytometric analysis on peripheral blood mononuclear cells (PBMC); we collected from 23 healthy donors and 225 MS patients: untreated (n = 19) or treated with NTZ (n = 113), interferon-beta (n = 26), glatiramer acetate (n = 26), fingolimod (n = 23) and rituximab (n = 18). We have also analysed two PML/IRIS (immune reconstitution inflammatory syndrome) patients and four longitudinal samples of a NTZ-treated patients before and during the development of a clinical asymptomatic magnetic resonance imaging (MRI) lesion confirmed as PML by cerebrospinal fluid (CSF) examination. Thirty-five NTZ-treated patients were studied longitudinally with three samples taken 4 months apart. Results: The NTZ-treated patients showed a lower percentage of CD62L (33.68 %, n = 113) than first-line treated patients (44.24 %, n = 52, p = 0.0004). NTZ effect was already clear during the first year of treatment (34.68 %; p = 0.0184); it persisted in the following years and disappeared after drug withdrawal (44.08 %). Three percent of longitudinally analysed patients showed a percentage of CD62LCD4+ T cells under a hypothetical threshold and one patient with asymptomatic PML belongs to a group which expressed low percentage of CD62LCD4+ T cells. Conclusions: Our research confirms that NTZ has a specific effect on CD62LCD4+ T cells consisting in decreasing of the number of positive cells. The low level of CD62L found in a clinically asymptomatic PML patient strengthens its potential usefulness as a biomarker of high PML risk in NTZ-treated patients. A larger study is required to better confirm the data

Novel homozygous GBA2 mutation in a patient with complicated spastic paraplegia

Hereditary spastic paraplegias (HSPs) are a heterogeneous group of neurological disorders characterized primarily by a pyramidal syndrome with lower limb spasticity, which can manifest as pure HSP or associated with a number of neurological or non-neurological signs (i.e., complicated HSPs). The clinical variability of HSPs is associated with a wide genetic heterogeneity, with more than eighty causative genes known. Recently, next generation sequencing (NGS) has allowed increasing genetic definition in such a heterogeneous group of disorders. We report on a 56- year-old man affected by sporadic complicated HSP consisting of a pyramidal syndrome, cerebellar ataxia, congenital cataract, pes cavus, axonal sensory-motor peripheral neuropathy and cognitive decline. Brain MRI showed cerebellar atrophy and thin corpus callosum. By NGS we found a novel homozygous biallelic c.452-1G > C mutation in the b-glucosidase 2 gene (GBA2), known to be causative for autosomal recessive hereditary spastic paraplegia type 46 (SPG46). The rarity of this inherited form besides reporting on a novel mutation, expands the genetic and clinical spectrum of SPG46 related HSP

Machine learning-based in-band OSNR estimation from optical spectra

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Measuring the optical signal to noise ratio (OSNR) at certain network points is essential for failure handling, for single connection but also global network optimization. Estimating OSNR is inherently difficult in dense wavelength routed networks, where connections accumulate noise over different paths and tight filters do not allow the observation of the noise level at signal sides. We propose an in-band OSNR estimation process, which relies on a machine learning (ML) method, in particular on Gaussian process (GP) or support vector machine (SVM) regression. We acquired high-resolution optical spectra, through an experimental setup, using a Brillouin optical spectrum analyzer (BOSA), on which we applied our method and obtained excellent estimation accuracy. We also verified the accuracy of this approach for various resolution scenarios. To further validate it, we generated spectral data for different configurations and resolutions through simulations. This second validation confirmed the estimation quality of the proposed approach.The authors would like to thank Aragon Photonics Labs for providing the BOSA used for the experiments. This work was partially funded by the ONFIRE project supported by EU Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 765275Peer ReviewedPostprint (author's final draft

Spectral processing techniques for efficient monitoring in optical networks

Having ubiquitous optical monitors in dense wavelength-division multiplexing (DWDM) or flex-grid networks allows the estimation in real time of crucial parameters. Such monitoring would be even more important in disaggregated optical networks, to inspect performance issues related to inter-vendor interoperability. Several important parameters can be retrieved using optical spectrum analyzers (OSAs). However, omnipresent OSAs represent an infeasible solution. Nevertheless, the advent of new, relatively cheap, compact and medium-resolution optical channel monitors (OCMs) enable a more intensive deployment of these devices. In this paper, we identify two main scenarios for the placement of such monitors: at the ingress and at the egress of the optical nodes. In the ingress scenario, we can directly estimate the parameters related to the signals, but not those related to the filters. On the contrary, in the egress scenario, the filter-related parameters can be easily detected, but not those related to amplified spontaneous emission. Therefore, we present two methods that, leveraging a curve fitting and a machine learning regression algorithm, allow detection of the missing parameters. We verify the proposed solutions with spectral data acquired in simulation and experimental setups. We obtained good estimation accuracy for both setups and for both studied placement scenarios. It is noteworthy that in the experimental assessment of the ingress scenario, we achieved a maximum absolute error (MAE) lower than 1 GHz in filter bandwidth estimation and a MAE lower than 0.5 GHz in filter frequency shift estimation. In addition, by comparing the relative errors of the considered parameters, we identified the ingress scenario as the more beneficial. In particular, we estimated the filter central frequency shift with 84% and the filter 6 dB bandwidth with 75% higher accuracy, with respect to datasheet/reference values. This translates into a total reduction of the estimated signal-to-noise ratio (SNR) penalty, introduced by a single optical filter, of 0.24 dB.Funding: Horizon 2020 Framework Programme (765275). This work is part of the Future Optical Networks for Innovation, Research and Experimentation (ONFIRE) project (https://h2020-onfire.eu), which is supported by the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie Action.Peer ReviewedPostprint (author's final draft

A non-conserved amino acid variant regulates differential signalling between human and mouse CD28

CD28 superagonistic antibodies (CD28SAb) can preferentially activate and expand immunosuppressive regulatory T cells (Treg) in mice. However, pre-clinical trials assessing CD28SAbs for the therapy of autoimmune diseases reveal severe systemic inflammatory response syndrome in humans, thereby implying the existence of distinct signalling abilities between human and mouse CD28. Here, we show that a single amino acid variant within the C-terminal proline-rich motif of human and mouse CD28 (P212 in human vs. A210 in mouse) regulates CD28-induced NF-κB activation and pro-inflammatory cytokine gene expression. Moreover, this Y209APP212 sequence in humans is crucial for the association of CD28 with the Nck adaptor protein for actin cytoskeleton reorganisation events necessary for CD28 autonomous signalling. This study thus unveils different outcomes between human and mouse CD28 signalling to underscore the importance of species difference when transferring results from preclinical models to the bedside

Feedback-Based Channel Frequency Optimization in Superchannels

Superchannels leverage the flexibility of elastic optical networks and pave the way to higher capacity channels in space division multiplexing (SDM) networks. A superchannel consists of subchannels to which continuous spectral grid slots are assigned. To guarantee superchannel operation, we need to account for soft failures, e.g., laser drifts causing interference between subchannels, wavelength-dependent performance variations, and filter misalignments affecting the edge subchannels. This is achieved by reserving spectral guardband between subchannels or by employing a lower modulation format. We propose a process that dynamically retunes the subchannel transmitter (TX) lasers to compensate for soft failures during operation and optimizes the total capacity or the minimum subchannel quality of transmission (QoT) performance. We use an iterative stochastic subgradient method that at each iteration probes the network and leverages monitoring information, particularly subchannels signal-to-noise ratio (SNR) values, to optimize the TX frequencies. Our results indicate that our proposed method always approaches the optima found with an exhaustive search technique, unsuitable for operating networks, irrespective of the subchannel number, modulation format, roll-off factor, filters bandwidth, and starting frequencies. Considering a four-subchannel superchannel, the proposed method achieves 2.47 dB and 3.73 dB improvements for a typical soft failure of +/- 2 GHz subchannel frequency drifts around the optimum, for the two examined objectives

Antitumor immunization of mothers delays tumor development in cancer-prone offspring

Maternal immunization is successfully applied against some life-threatening infectious diseases as it can protect the mother and her offspring through the passive transfer of maternal antibodies. Here, we sought to evaluate whether the concept of maternal immunization could also be applied to cancer immune-prevention. We have previously shown that antibodies induced by DNA vaccination against rat Her2 (neu) protect heterozygous neu-transgenic female (BALB-neuT) mice from autochthonous mammary tumor development. We, herein, seek to evaluate whether a similar maternal immunization can confer antitumor protection to BALB-neuT offspring. Significantly extended tumor-free survival was observed in BALB-neuT offspring born and fed by mothers vaccinated against neu, as compared to controls. Maternally derived anti-neu immunoglobulin G (IgG) was successfully transferred from mothers to newborns and was responsible for the protective effect. Vaccinated mothers and offspring also developed active immunity against neu as revealed by the presence of T–cell-mediated cytotoxicity against the neu immunodominant peptide. This active response was due to the milk transfer of immune complexes that were formed between the neu extracellular domain, shed from vaccine-transfected muscle cells, and the anti-neu IgG induced by the vaccine. These findings show that maternal immunization has the potential to hamper mammary cancer in genetically predestinated offspring and to develop into applications against lethal neonatal cancer diseases for which therapeutic options are currently unavailable