Effect of anti-IgE therapy on food allergen specific T cell responses in eosinophil associated gastrointestinal disorders

<p>Abstract</p> <p>Background</p> <p>Anti-IgE therapy inhibits mast cell and basophil activation, blocks IgE binding to both FcεRI and CD23 and down regulates FcεRI expression by antigen (Ag) presenting cells (APCs). In addition to its classical role in immediate hypersensitivity, IgE has been shown <it>in vitro </it>to facilitate Ag presentation of allergens, whereby APC bound IgE preferentially takes up allergens for subsequent processing and presentation. The purpose of this study was to determine whether anti-IgE therapy, by blocking facilitated Ag presentation <it>in vivo</it>, attenuates allergen specific Th2 cell responses.</p> <p>Methods</p> <p>To test this hypothesis, food allergen specific T cell responses were examined during a 16-week clinical trial of omalizumab in nine subjects with eosinophilic gastroenteritis and food sensitization. Allergen specific T cell responses were measured using carboxyfluorescein succinimidyl ester dye dilution coupled with intracellular cytokine staining and polychromatic flow cytometry. Four independent indices of allergen specific T cell response (proliferation, Ag dose response, precursor frequency, and the ratio of Th2:Th1 cytokine expression) were determined.</p> <p>Results</p> <p>Eight of the 9 subjects had measurable food allergen specific responses, with a median proliferation index of 112-fold. Allergen specific T cell proliferation was limited to CD4 T cells, whereas CD8 T cell did not proliferate. Food allergen specific responses were Th2 skewed relative to tetanus specific responses in the same subjects. In contradistinction to the original hypothesis, anti-IgE treatment did not diminish any of the four measured indices of allergen specific T cell response.</p> <p>Conclusions</p> <p>In sum, using multiple indices of T cell function, this study failed to demonstrate that anti-IgE therapy broadly or potently inhibits allergen specific T cell responses. As such, these data do not support a major role for IgE facilitated Ag presentation augmenting allergen specific T cell responses <it>in vivo</it>.</p> <p>Trial registration</p> <p>ClinicalTrials.gov identifier <a href="http://www.clinicaltrials.gov/ct2/show/NCT00084097">NCT00084097</a></p

PPARγ and PPARδ as Modulators of Neoplasia and Cell Fate

PPARγ and PPARδ agonists represent unique classes of drugs that act through their ability to modulate gene transcription associated with intermediary metabolism, differentiation, tumor suppression, and in some instances proliferation and cell adhesion. PPARγ agonists are used by millions of people each year to treat type 2 diabetes but may also find additional utility as relatively nontoxic potentiators of chemotherapy. PPARδ agonists produce complex actions as shown by their tumor promoting effects in rodents and their cholesterol-lowering action in dyslipidemias. There is now emerging evidence that PPARs regulate tumor suppressor genes and developmental pathways associated with transformation and cell fate determination. This review discusses the role of PPARγ and PPARδ agonists as modulators of these processes

3-Phosphoinositide-dependent Protein Kinase-1 (PDK1) promotes invasion and activation of matrix metalloproteinases

BACKGROUND: Metastasis is a major cause of morbidity and mortality in breast cancer with tumor cell invasion playing a crucial role in the metastatic process. PDK1 is a key molecule that couples PI3K to cell proliferation and survival signals in response to growth factor receptor activation, and is oncogenic when expressed in mouse mammary epithelial cells. We now present evidence showing that PDK1-expressing cells exhibit enhanced anchorage-dependent and -independent cell growth and are highly invasive when grown on Matrigel. These properties correlate with induction of MMP-2 activity, increased MT1-MMP expression and a unique gene expression profile. METHODS: Invasion assays in Matrigel, MMP-2 zymogram analysis, gene microarray analysis and mammary isografts were used to characterize the invasive and proliferative function of cells expressing PDK1. Tissue microarray analysis of human breast cancers was used to measure PDK1 expression in invasive tumors by IHC. RESULTS: Enhanced invasion on Matrigel in PDK1-expressing cells was accompanied by increased MMP-2 activity resulting from stabilization against proteasomal degradation. Increased MMP-2 activity was accompanied by elevated levels of MT1-MMP, which is involved in generating active MMP-2. Gene microarray analysis identified increased expression of the ECM-associated genes decorin and type I procollagen, whose gene products are substrates of MT1-MMP. Mammary fat pad isografts of PDK1-expressing cells produced invasive adenocarcinomas. Tissue microarray analysis of human invasive breast cancer indicated that PDK1pSer241 was strongly expressed in 90% of samples. CONCLUSION: These results indicate that PDK1 serves as an important effector of mammary epithelial cell growth and invasion in the transformed phenotype. PDK1 mediates its effect in part by MT1-MMP induction, which in turn activates MMP-2 and modulates the ECM proteins decorin and collagen. The presence of increased PDK1 expression in the majority of invasive breast cancers suggests its importance in the metastatic process

Bidirectionally Deformable Motion Modulation For Video-based Human Pose Transfer

Video-based human pose transfer is a video-to-video generation task that animates a plain source human image based on a series of target human poses. Considering the difficulties in transferring highly structural patterns on the garments and discontinuous poses, existing methods often generate unsatisfactory results such as distorted textures and flickering artifacts. To address these issues, we propose a novel Deformable Motion Modulation (DMM) that utilizes geometric kernel offset with adaptive weight modulation to simultaneously perform feature alignment and style transfer. Different from normal style modulation used in style transfer, the proposed modulation mechanism adaptively reconstructs smoothed frames from style codes according to the object shape through an irregular receptive field of view. To enhance the spatio-temporal consistency, we leverage bidirectional propagation to extract the hidden motion information from a warped image sequence generated by noisy poses. The proposed feature propagation significantly enhances the motion prediction ability by forward and backward propagation. Both quantitative and qualitative experimental results demonstrate superiority over the state-of-the-arts in terms of image fidelity and visual continuity. The source code is publicly available at github.com/rocketappslab/bdmm.Comment: ICCV 202

SVCNet: Scribble-based Video Colorization Network with Temporal Aggregation

In this paper, we propose a scribble-based video colorization network with temporal aggregation called SVCNet. It can colorize monochrome videos based on different user-given color scribbles. It addresses three common issues in the scribble-based video colorization area: colorization vividness, temporal consistency, and color bleeding. To improve the colorization quality and strengthen the temporal consistency, we adopt two sequential sub-networks in SVCNet for precise colorization and temporal smoothing, respectively. The first stage includes a pyramid feature encoder to incorporate color scribbles with a grayscale frame, and a semantic feature encoder to extract semantics. The second stage finetunes the output from the first stage by aggregating the information of neighboring colorized frames (as short-range connections) and the first colorized frame (as a long-range connection). To alleviate the color bleeding artifacts, we learn video colorization and segmentation simultaneously. Furthermore, we set the majority of operations on a fixed small image resolution and use a Super-resolution Module at the tail of SVCNet to recover original sizes. It allows the SVCNet to fit different image resolutions at the inference. Finally, we evaluate the proposed SVCNet on DAVIS and Videvo benchmarks. The experimental results demonstrate that SVCNet produces both higher-quality and more temporally consistent videos than other well-known video colorization approaches. The codes and models can be found at https://github.com/zhaoyuzhi/SVCNet.Comment: accepted by IEEE Transactions on Image Processing (TIP

VCGAN: Video Colorization with Hybrid Generative Adversarial Network

We propose a hybrid recurrent Video Colorization with Hybrid Generative Adversarial Network (VCGAN), an improved approach to video colorization using end-to-end learning. The VCGAN addresses two prevalent issues in the video colorization domain: Temporal consistency and unification of colorization network and refinement network into a single architecture. To enhance colorization quality and spatiotemporal consistency, the mainstream of generator in VCGAN is assisted by two additional networks, i.e., global feature extractor and placeholder feature extractor, respectively. The global feature extractor encodes the global semantics of grayscale input to enhance colorization quality, whereas the placeholder feature extractor acts as a feedback connection to encode the semantics of the previous colorized frame in order to maintain spatiotemporal consistency. If changing the input for placeholder feature extractor as grayscale input, the hybrid VCGAN also has the potential to perform image colorization. To improve the consistency of far frames, we propose a dense long-term loss that smooths the temporal disparity of every two remote frames. Trained with colorization and temporal losses jointly, VCGAN strikes a good balance between color vividness and video continuity. Experimental results demonstrate that VCGAN produces higher-quality and temporally more consistent colorful videos than existing approaches.Comment: Submitted Major Revision Manuscript of IEEE Transactions on Multimedia (TMM