Rôle de l’inflammation alvéolaire dans la survenue et l'aggravation de la pneumopathie interstitielle diffuse au cours de la sclérodermie systémique

Summary not transmittedLe dysfonctionnement endothélial et le dérèglement du système immunitaire sont les deux principaux mécanismes physiopathologiques responsables de la fibrose de la peau et des organes internes dans la sclérodermie systémique (ScS). La pneumopathie interstitielle diffuse (PID) est devenue la principale cause de mortalité de la maladie. L'inflammation pulmonaire est la conséquence de l'activation du système immunitaire, qui stimule la NO synthase inductible (NOS-2) et augmente la production alvéolaire de monoxyde d'azote (NO). L'augmentation de la concentration alvéolaire de NO (CANO) est significativement corrélée à la sévérité de la PID chez les patients atteints de ScS. L'augmentation de la CANO est liée à l'effet inducteur du sérum des malades sur la prolifération des fibroblastes pulmonaires et leur différentiation en myofibroblastes, faisant ainsi le lien biologique entre l'inflammation alvéolaire et la fibrose pulmonaire dans la ScS. Nous avons ensuite testé la valeur prédictive de la CANO dans la détérioration de la PID. Les patients ayant une CANO supérieure à 5,3 ppb présentent un risque élevé (> 6 fois) de voir survenir l'aggravation de la fibrose pulmonaire ou le décès (évènement combiné) par rapport à ceux qui ont une CANO inférieure ou égale à 5,3 ppb. Une valeur de CANO supérieure ou égale à 8,5 ppb permet de détecter les patients avec un risque de 90% de survenue d'évènement combiné dans les trois ans. Ces patients pourraient alors bénéficier d'un traitement approprié précoce. Nous avons évalué l'inflammation pulmonaire dans deux modèles murins de fibrose pulmonaire induite par l'acide hypochloreux et la bléomycine, par la mesure non-invasive du NO expiré (FENO). Le pic d'augmentation de FENO se situe 4 semaines après le début des injections, et précède la fibrose pulmonaire, qui ne devient significative qu'à partir de 6 semaines d'intoxication. L'augmentation de la FENO est liée à l'augmentation de l'expression de la NOS-2 aussi bien aux niveaux des bronches qu'aux niveaux des alvéoles. Enfin, la forte production de NO constatée provoque un effet délétère direct sur le tissu pulmonaire attesté par la présence de 3-nitrotyrosines, marqueurs du stress nitrosatif.Mots-clés: sclérodermie systémique, pneumopathie interstitielle diffuse, monoxyde d'azote, physiopathologie

Inductive and Transductive Few-Shot Video Classification via Appearance and Temporal Alignments

We present a novel method for few-shot video classification, which performs appearance and temporal alignments. In particular, given a pair of query and support videos, we conduct appearance alignment via frame-level feature matching to achieve the appearance similarity score between the videos, while utilizing temporal order-preserving priors for obtaining the temporal similarity score between the videos. Moreover, we introduce a few-shot video classification framework that leverages the above appearance and temporal similarity scores across multiple steps, namely prototype-based training and testing as well as inductive and transductive prototype refinement. To the best of our knowledge, our work is the first to explore transductive few-shot video classification. Extensive experiments on both Kinetics and Something-Something V2 datasets show that both appearance and temporal alignments are crucial for datasets with temporal order sensitivity such as Something-Something V2. Our approach achieves similar or better results than previous methods on both datasets. Our code is available at https://github.com/VinAIResearch/fsvc-ata.Comment: Accepted to ECCV 202

Domestic violence crisis identification from Facebook posts based on deep learning

Domestic Violence (DV) is a cause of concern due to the threat it poses towards public health and human rights. There is a need for quick identification of the victims of this condition, so that Domestic Violence Crisis Service (DVCS) can offer necessary support in a timely manner. The availability of social media has allowed DV victims to share their stories and receive support from community, which opens an opportunity for DVCS to actively approach and support DV victims. However, it is time consuming and inefficient to manually browse through a massive number of available posts. This paper adopts a Deep Learning as an approach for automatic identification of DV victims in critical need. Empirical evidence on a ground truth data set has achieved an accuracy of up to 94%, which outperforms traditional machine learning techniques. Analysis of informative features helps to identify important words which might indicate critical posts in the classification process. The experimental results are helpful to researchers and practitioners in developing techniques for identifying and supporting DV victims

Picturing One\u27s Self: Camera Use in Zoom Classes during the COVID-19 Pandemic

Starting from the spring of 2020, higher institutions in the US underwent a rapid shift from in-person classes to emergency remote education, in response to the COVID-19 outbreak. Under this circumstance, a variety of video conferencing tools (e.g., Zoom) have been adopted for distance education, which pose a set of new challenges arising from synchronous online classes. Among these, one significant issue was students\u27 unwillingness to open cameras, resulting in a lack of non-verbal cues that instructors could rely on to gauge students\u27 understanding and adjust their teachings. Towards addressing this issue, our qualitative study aims at investigating the rationales behind students\u27 camera avoidance. Through a series of semi-structured interviews on undergraduate students in the U.S, we identified prominent factors -- namely the class size, lecture style, level of interactivity and privacy concerns -- that influenced students\u27 motivation for opening their cameras. At the same time, we uncovered several difficulties, such as heightened self-awareness, feeling of minority and academic perspective, that discouraged students from opening camera, with more substantial impacts on international students. We conclude with actionable insights into the design of online classes, video-conferencing platforms and camera technology that can promote camera usage, thereby contributing to scalable and inclusive interventions for facilitating the transition into remote education

Single-machine Scheduling with Splitable Jobs and Availability Constraints

This paper deals with a single machine scheduling problem with availability constraints. The jobs are splitable and lower bound on the size of each sub-job is imposed. The objective is to find a feasible schedule that minimizes the makespan. The proposed scheduling problem is proved to be NP-hard in the strong sense. Some effective heuristic algorithms are then proposed. Additionally, computational results show that the proposed heuristic performs well

Gene therapy in patient-specific stem cell lines and a preclinical model of retinitis pigmentosa with membrane frizzled-related protein defects

Defects in Membrane Frizzled-related Protein (MFRP) cause autosomal recessive retinitis pigmentosa (RP). MFRP codes for a retinal pigment epithelium (RPE)-specific membrane receptor of unknown function. In patient-specific induced pluripotent stem (iPS)-derived RPE cells, precise levels of MFRP, and its dicistronic partner CTRP5, are critical to the regulation of actin organization. Overexpression of CTRP5 in naive human RPE cells phenocopied behavior of MFRP-deficient patient RPE (iPS-RPE) cells. AAV8 (Y733F) vector expressing human MFRP rescued the actin disorganization phenotype and restored apical microvilli in patient-specific iPS-RPE cell lines. As a result, AAV-treated MFRP mutant iPS-RPE recovered pigmentation and transepithelial resistance. The efficacy of AAV-mediated gene therapy was also evaluated in Mfrp(rd6)/Mfrp(rd6) mice--an established preclinical model of RP--and long-term improvement in visual function was observed in AAV-Mfrp-treated mice. This report is the first to indicate the successful use of human iPS-RPE cells as a recipient for gene therapy. The observed favorable response to gene therapy in both patient-specific cell lines, and the Mfrp(rd6)/Mfrp(rd6) preclinical model suggests that this form of degeneration caused by MFRP mutations is a potential target for interventional trials

Differences in K-ras and mitochondrial DNA mutations and microsatellite instability between colorectal cancers of Vietnamese and Japanese patients

[Background]:The incidence of early-onset (under 50 years of age) colorectal cancer (CRC) in the Vietnamese has been reported to be quite higher than that in the Japanese. To clarify the differences in genetic alterations between Vietnamese and Japanese CRCs, we investigated mutations in K-ras and mitochondrial DNA (mtDNA) and high-frequency microsatellite instability (MSI-H) in the CRCs of Vietnamese and Japanese patients. [Methods]:We enrolled 60 Vietnamese and 233 Japanese patients with invasive CRCs. DNA was extracted from formalin-fixed, paraffin-embedded tissue sections. K-ras mutations were examined with PCR-single-strand conformation polymorphism analysis. mtDNA mutations and MSI-H were examined with microsatellite analysis using D310 and BAT-26, respectively. [Results]:K-ras mutations were examined in 60 Vietnamese and 45 Japanese CRCs. The frequency of the mutations in the Vietnamese CRCs was significantly higher than that in the Japanese CRCs (8 of 24 [33%] vs 5 of 45 [11%], p =0.048). MSI-H was examined in 60 Vietnamese and 130 Japanese CRCs. The frequency of MSI-H in the Vietnamese CRCs was also significantly higher than that in the Japanese CRCs (6 of 27 [22%] vs 10 of 130 [8%], p =0.030). mtDNA mutations were examined in 60 Vietnamese and 138 Japanese CRCs. The frequency of mtDNA mutations in the Vietnamese CRCs was significantly higher than that in the Japanese CRCs (19 of 44 [43%] vs 11 of 133 [9%], p <0.001). There were no significant differences in clinicopathologic characteristics, such as age, sex, tumour location, and depth, in terms of tumours with/without each genetic alteration in the CRCs of the Vietnamese and Japanese patients. [Conclusions]:These results indicate that the developmental pathways of CRCs in the Vietnamese may differ from those of CRCs in the Japanese

The new CCSDS standard for low-complexity lossless and near-lossless multispectral and hyperspectral image compression

This paper describes the emerging Issue 2 of the CCSDS-123.0-B standard for low-complexity compression of multispectral and hyperspectral imagery, focusing on its new features and capabilities. Most significantly, this new issue incorporates a closed-loop quantization scheme to provide near-lossless compression capability while still supporting lossless compression, and introduces a new entropy coding option that provides better compression of low-entropy data

The new CCSDS standard for low-complexity lossless and near-lossless multispectral and hyperspectral image compression

This paper describes the emerging Issue 2 of the CCSDS-123.0-B standard for low-complexity compression of multispectral and hyperspectral imagery, focusing on its new features and capabilities. Most significantly, this new issue incorporates a closed-loop quantization scheme to provide near-lossless compression capability while still supporting lossless compression, and introduces a new entropy coding option that provides better compression of low-entropy data

Open X-Embodiment:Robotic learning datasets and RT-X models

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io