Verifying Client Media Playback using Unique Embedded Metadata

The described subject matter is directed to injecting metadata into a media stream at (or just after) a cache edge of a content delivery network (“CDN”). A unique instance value (e.g., included within a tag or uniform resource locator (“URL”)), is embedded by an edge device into metadata for the media stream. Examples of media stream metadata include, but are not limited to, D3 timed metadata inserted in an MPEG-2 transport stream or an emsg box in the ISO-BMFF video container for MPEG-DASH. When a streaming media player receives the metadata, it generates a network request or callback request including the tag or directed to the embedded URL. A server receiving this message can use the unique instance value as confirmation that the player received and processed the metadata, which indicates that media content delivered with the metadata was presented by the media player. The server can then authorize additional media delivery and/or generate reliable presentation statistics for the content

Mysins : Make Your Semantic INformation System

Article court accompagnant une démonstration logicielle. I.S.B.N. : 9782854289220International audienceLa sémantique est de plus en plus utilisée dans différents domaines comme la recherche d'information (RI) et le Web sémantique. Dans le domaine de la RI, différents participants interviennent : des fournisseurs d'informations et des utilisateurs. L'utilisation de la sémantique nécessite la mise en œuvre de mécanismes précis. En RI, il s'agit entre autre de l'utilisation d'ontologies, du calcul de similarité et de l'indexation. L'étude de chacun de ces axes nécessite un effort important de synthèse et d'intégration. Pour palier le manque évident d'une architecture générique distribuée pour la conception de systèmes d'information sémantiques, nous proposons un framework : Mysins

The Impact of Different Antibiotic Regimens on the Emergence of Antimicrobial-Resistant Bacteria

Backgroud: The emergence and ongoing spread of antimicrobial-resistant bacteria is a major public health threat. Infections caused by antimicrobial-resistant bacteria are associated with substantially higher rates of morbidity and mortality compared to infections caused by antimicrobial-susceptible bacteria. The emergence and spread of these bacteria is complex and requires incorporating numerous interrelated factors which clinical studies cannot adequately address. Methods/Principal Findings: A model is created which incorporates several key factors contributing to the emergence and spread of resistant bacteria including the effects of the immune system, acquisition of resistance genes and antimicrobial exposure. The model identifies key strategies which would limit the emergence of antimicrobial-resistant bacterial strains. Specifically, the simulations show that early initiation of antimicrobial therapy and combination therapy with two antibiotics prevents the emergence of resistant bacteria, whereas shorter courses of therapy and sequential administration of antibiotics promote the emergence of resistant strains. Conclusions/Significance: The principal findings suggest that (i) shorter lengths of antibiotic therapy and early interruption of antibiotic therapy provide an advantage for the resistant strains, (ii) combination therapy with two antibiotics prevents the emergence of resistance strains in contrast to sequential antibiotic therapy, and (iii) early initiation of antibiotics is among the most important factors preventing the emergence of resistant strains. These findings provide new insights into strategies aimed at optimizing the administration of antimicrobials for the treatment of infections and the prevention of the emergence of antimicrobial resistance

In vitro and in vivo antifungal profile of a novel and long acting inhaled azole, PC945, on Aspergillus fumigatus infection

The profile of PC945, a novel triazole antifungal, designed for administration via inhalation, hasbeen assessed in a range of in vitro and in vivo studies. PC945 was characterized as a potent, tight-binding inhibitor of Aspergillus fumigatus sterol 14α-demethylase (CYP51A and CYP51B)activity.In addition, when A. fumigatus hyphae or human bronchial cells were treated with PC945, and thenwashed, PC945 was found to be quickly absorbed into both target and non-target cells and toproduce persistent antifungal effects. In temporarily neutropenic immunocompromised miceinfected with A. fumigatus intranasally, 50% of the animals survived until day 7 when treatedintranasally with PC945 at 0.56 μg/mouse, while posaconazole showed similar effects (44%) at14 μg/mouse. This profile affirms that topical treatment with PC945 should provide potentantifungal activity in the lung

Whole Genome Deep Sequencing of HIV-1 Reveals the Impact of Early Minor Variants Upon Immune Recognition During Acute Infection

Deep sequencing technologies have the potential to transform the study of highly variable viral pathogens by providing a rapid and cost-effective approach to sensitively characterize rapidly evolving viral quasispecies. Here, we report on a high-throughput whole HIV-1 genome deep sequencing platform that combines 454 pyrosequencing with novel assembly and variant detection algorithms. In one subject we combined these genetic data with detailed immunological analyses to comprehensively evaluate viral evolution and immune escape during the acute phase of HIV-1 infection. The majority of early, low frequency mutations represented viral adaptation to host CD8+ T cell responses, evidence of strong immune selection pressure occurring during the early decline from peak viremia. CD8+ T cell responses capable of recognizing these low frequency escape variants coincided with the selection and evolution of more effective secondary HLA-anchor escape mutations. Frequent, and in some cases rapid, reversion of transmitted mutations was also observed across the viral genome. When located within restricted CD8 epitopes these low frequency reverting mutations were sufficient to prime de novo responses to these epitopes, again illustrating the capacity of the immune response to recognize and respond to low frequency variants. More importantly, rapid viral escape from the most immunodominant CD8+ T cell responses coincided with plateauing of the initial viral load decline in this subject, suggestive of a potential link between maintenance of effective, dominant CD8 responses and the degree of early viremia reduction. We conclude that the early control of HIV-1 replication by immunodominant CD8+ T cell responses may be substantially influenced by rapid, low frequency viral adaptations not detected by conventional sequencing approaches, which warrants further investigation. These data support the critical need for vaccine-induced CD8+ T cell responses to target more highly constrained regions of the virus in order to ensure the maintenance of immunodominant CD8 responses and the sustained decline of early viremia

Systems Biology Approaches Reveal a Specific Interferon-Inducible Signature in HTLV-1 Associated Myelopathy

Human T-lymphotropic virus type 1 (HTLV-1) is a retrovirus that persists lifelong in the host. In ∼4% of infected people, HTLV-1 causes a chronic disabling neuroinflammatory disease known as HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). The pathogenesis of HAM/TSP is unknown and treatment remains ineffective. We used gene expression microarrays followed by flow cytometric and functional assays to investigate global changes in blood transcriptional profiles of HTLV-1-infected and seronegative individuals. We found that perturbations of the p53 signaling pathway were a hallmark of HTLV-1 infection. In contrast, a subset of interferon (IFN)-stimulated genes was over-expressed in patients with HAM/TSP but not in asymptomatic HTLV-1 carriers or patients with the clinically similar disease multiple sclerosis. The IFN-inducible signature was present in all circulating leukocytes and its intensity correlated with the clinical severity of HAM/TSP. Leukocytes from patients with HAM/TSP were primed to respond strongly to stimulation with exogenous IFN. However, while type I IFN suppressed expression of the HTLV-1 structural protein Gag it failed to suppress the highly immunogenic viral transcriptional transactivator Tax. We conclude that over-expression of a subset of IFN-stimulated genes in chronic HTLV-1 infection does not constitute an efficient host response but instead contributes to the development of HAM/TSP

Epileptic Seizure Forecasting with Generative Adversarial Networks

Many outstanding studies have reported promising results in seizure forecasting, one of the most challenging predictive data analysis problems. This is mainly because electroencephalogram (EEG) bio-signal intensity is very small, in $\mu \text{V}$ range, and there are significant sensing difficulties given physiological and non-physiological artifacts. Today the process of accurate epileptic seizure identification and data labeling is done by neurologists. The current unpredictability of epileptic seizure activities together with the lack of reliable treatment for patients living with drug resistant forms of epilepsy creates an urgency for research into accurate, sensitive and patient-specific seizure forecasting. Most seizure forecasting algorithms use only labeled data for training purposes. As the seizure data is labeled manually by neurologists, preparing the labeled data is expensive and time consuming, making the best use of the data critical. In this article, we propose an approach that can make use of not only labeled EEG signals but also the unlabeled ones which are more accessible. We use the short-time Fourier transform on 28-s EEG windows as a pre-processing step. A generative adversarial network (GAN) is trained in an unsupervised manner where information of seizure onset is disregarded. The trained Discriminator of the GAN is then used as a feature extractor. Features generated by the feature extractor are classified by two fully-connected layers (can be replaced by any classifier) for the labeled EEG signals. This semi-supervised patient-specific seizure forecasting method achieves an out-of-sample testing area under the operating characteristic curve (AUC) of 77.68%, 75.47% and 65.05% for the CHB-MIT scalp EEG dataset, the Freiburg Hospital intracranial EEG dataset and the EPILEPSIAE dataset, respectively. Unsupervised training without the need for labeling is important because not only it can be performed in real-time during EEG signal recording, but also it does not require feature engineering effort for each patient. To the best of our knowledge, this is the first application of GAN to seizure forecasting

A 380-gene meta-signature of active tuberculosis compared with healthy controls.

Eur Respir J 2016 Jun; 47(6):1873-