2,407 research outputs found

    Dexamethasone induces apoptosis in pulmonary arterial smooth muscle cells

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    BACKGROUND: Dexamethasone suppressed inflammation and haemodynamic changes in an animal model of pulmonary arterial hypertension (PAH). A major target for dexamethasone actions is NF-κB, which is activated in pulmonary vascular cells and perivascular inflammatory cells in PAH. Reverse remodelling is an important concept in PAH disease therapy, and further to its anti-proliferative effects, we sought to explore whether dexamethasone augments pulmonary arterial smooth muscle cell (PASMC) apoptosis. METHODS: Analysis of apoptosis markers (caspase 3, in-situ DNA fragmentation) and NF-κB (p65 and phospho-IKK-α/β) activation was performed on lung tissue from rats with monocrotaline (MCT)-induced pulmonary hypertension (PH), before and after day 14–28 treatment with dexamethasone (5 mg/kg/day). PASMC were cultured from this rat PH model and from normal human lung following lung cancer surgery. Following stimulation with TNF-α (10 ng/ml), the effects of dexamethasone (10(−8)–10(−6) M) and IKK2 (NF-κB) inhibition (AS602868, 0–3 μM (0-3×10(−6) M) on IL-6 and CXCL8 release and apoptosis was determined by ELISA and by Hoechst staining. NF-κB activation was measured by TransAm assay. RESULTS: Dexamethasone treatment of rats with MCT-induced PH in vivo led to PASMC apoptosis as displayed by increased caspase 3 expression and DNA fragmentation. A similar effect was seen in vitro using TNF-α-simulated human and rat PASMC following both dexamethasone and IKK2 inhibition. Increased apoptosis was associated with a reduction in NF-κB activation and in IL-6 and CXCL8 release from PASMC. CONCLUSIONS: Dexamethasone exerted reverse-remodelling effects by augmenting apoptosis and reversing inflammation in PASMC possibly via inhibition of NF-κB. Future PAH therapies may involve targeting these important inflammatory pathways

    Graph Distillation for Action Detection with Privileged Modalities

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    We propose a technique that tackles action detection in multimodal videos under a realistic and challenging condition in which only limited training data and partially observed modalities are available. Common methods in transfer learning do not take advantage of the extra modalities potentially available in the source domain. On the other hand, previous work on multimodal learning only focuses on a single domain or task and does not handle the modality discrepancy between training and testing. In this work, we propose a method termed graph distillation that incorporates rich privileged information from a large-scale multimodal dataset in the source domain, and improves the learning in the target domain where training data and modalities are scarce. We evaluate our approach on action classification and detection tasks in multimodal videos, and show that our model outperforms the state-of-the-art by a large margin on the NTU RGB+D and PKU-MMD benchmarks. The code is released at http://alan.vision/eccv18_graph/.Comment: ECCV 201

    Low-Rank Subspace Override for Unsupervised Domain Adaptation

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    Current supervised learning models cannot generalize well across domain boundaries, which is a known problem in many applications, such as robotics or visual classification. Domain adaptation methods are used to improve these generalization properties. However, these techniques suffer either from being restricted to a particular task, such as visual adaptation, require a lot of computational time and data, which is not always guaranteed, have complex parameterization, or expensive optimization procedures. In this work, we present an approach that requires only a well-chosen snapshot of data to find a single domain invariant subspace. The subspace is calculated in closed form and overrides domain structures, which makes it fast and stable in parameterization. By employing low-rank techniques, we emphasize on descriptive characteristics of data. The presented idea is evaluated on various domain adaptation tasks such as text and image classification against state of the art domain adaptation approaches and achieves remarkable performance across all tasks

    Economic footprint of California wildfires in 2018

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    Recent increases in the frequency and scale of wildfires worldwide have raised concerns about the influence of climate change and associated socioeconomic costs. In the western United States, the hazard of wildfire has been increasing for decades. Here, we use a combination of physical, epidemiological and economic models to estimate the economic impacts of California wildfires in 2018, including the value of destroyed and damaged capital, the health costs related to air pollution exposure and indirect losses due to broader economic disruption cascading along with regional and national supply chains. Our estimation shows that wildfire damages in 2018 totalled 148.5(126.1192.9)billion(roughly1.5148.5 (126.1–192.9) billion (roughly 1.5% of California’s annual gross domestic product), with 27.7 billion (19%) in capital losses, 32.2billion(2232.2 billion (22%) in health costs and 88.6 billion (59%) in indirect losses (all values in US$). Our results reveal that the majority of economic impacts related to California wildfires may be indirect and often affect industry sectors and locations distant from the fires (for example, 52% of the indirect losses—31% of total losses—in 2018 were outside of California). Our findings and methods provide new information for decision makers tasked with protecting lives and key production sectors and reducing the economic damages of future wildfires

    Channel selection for multispectral color imaging using binary differential evolution

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    2013-2014 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

    On the relative expressiveness of higher-order session processes

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    By integrating constructs from the λ-calculus and the π-calculus, in higher-order process calculi exchanged values may contain processes. This paper studies the relative expressiveness of HOπ, the higher-order π-calculus in which communications are governed by session types. Our main discovery is that HO, a subcalculus of HOπ which lacks name-passing and recursion, can serve as a new core calculus for session-typed higher-order concurrency. By exploring a new bisimulation for HO, we show that HO can encode HOπ fully abstractly (up to typed contextual equivalence) more precisely and efficiently than the first-order session π-calculus (π). Overall, under session types, HOπ, HO, and π are equally expressive; however, HOπ and HO are more tightly related than HOπ and π

    Growth/differentiation factor 15 causes TGFβ activated kinase 1 dependent muscle atrophy in pulmonary arterial hypertension

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    Introduction Skeletal muscle dysfunction is a clinically important complication of pulmonary arterial hypertension (PAH). Growth/differentiation factor 15 (GDF-15), a prognostic marker in PAH, has been associated with muscle loss in other conditions. We aimed to define the associations of GDF-15 and muscle wasting in PAH, to assess its utility as a biomarker of muscle loss and to investigate its downstream signalling pathway as a therapeutic target. Methods GDF-15 levels and measures of muscle size and strength were analysed in the monocrotaline (MCT) rat, Sugen/hypoxia mouse and in 30 patients with PAH. In C2C12 myotubes the downstream targets of GDF-15 were identified. The pathway elucidated was then antagonised in vivo. Results Circulating GDF-15 levels correlated with tibialis anterior (TA) muscle fibre diameter in the MCT rat (Pearson r=−0.61, p=0.003). In patients with PAH, plasma GDF-15 levels of <564 pg/L predicted those with preserved muscle strength with a sensitivity and specificity of ≥80%. In vitro GDF-15 stimulated an increase in phosphorylation of TGFβ-activated kinase 1 (TAK1). Antagonising TAK1, with 5(Z)-7-oxozeaenol, in vitro and in vivo led to an increase in fibre diameter and a reduction in mRNA expression of atrogin-1 in both C2C12 cells and in the TA of animals who continued to grow. Circulating GDF-15 levels were also reduced in those animals which responded to treatment. Conclusions Circulating GDF-15 is a biomarker of muscle loss in PAH that is responsive to treatment. TAK1 inhibition shows promise as a method by which muscle atrophy may be directly prevented in PAH
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