Non-influenza respiratory viruses in adult patients admitted with influenza-like illness: a 3-year prospective multicenter study.

PURPOSE: To describe the burden, and characteristics, of influenza-like illness (ILI) associated with non-influenza respiratory viruses (NIRV). METHODS: We performed a prospective, multicenter, observational study of adults admitted with ILI during three influenza seasons (2012-2015). Patients were screened for picornavirus, respiratory syncytial virus (RSV), coronavirus, human metapneumovirus, adenovirus, bocavirus, parainfluenza virus, and influenza, by PCR on nasopharyngeal samples. We excluded patients coinfected with NIRV and influenza. RESULTS: Among 1421 patients enrolled, influenza virus was detected in 535 (38%), and NIRV in 215 (15%), mostly picornavirus (n = 61), RSV (n = 53), coronavirus 229E (n = 48), and human metapneumovirus (n = 40). In-hospital mortality was 5% (NIRV), 4% (influenza), and 5% (no respiratory virus). As compared to influenza, NIRV were associated with age (median, 73 years vs. 68, P = 0.026), chronic respiratory diseases (53% vs. 45%, P = 0.034), cancer (14% vs. 9%, P = 0.029), and immunosuppressive drugs (21% vs. 14%, P = 0.028), and inversely associated with diabetes (18% vs. 25%, P = 0.038). On multivariable analysis, only chronic respiratory diseases (OR 1.5 [1.1-2.0], P = 0.008), and diabetes (OR 0.5 [0.4-0.8], P = 0.01) were associated with NIRV detection. CONCLUSIONS: NIRV are common in adults admitted with ILI during influenza seasons. Outcomes are similar in patients with NIRV, influenza, or no respiratory virus.

Semi-supervised segmentation of ultrasound images based on patch representation and continuous min cut.

Ultrasound segmentation is a challenging problem due to the inherent speckle and some artifacts like shadows, attenuation and signal dropout. Existing methods need to include strong priors like shape priors or analytical intensity models to succeed in the segmentation. However, such priors tend to limit these methods to a specific target or imaging settings, and they are not always applicable to pathological cases. This work introduces a semi-supervised segmentation framework for ultrasound imaging that alleviates the limitation of fully automatic segmentation, that is, it is applicable to any kind of target and imaging settings. Our methodology uses a graph of image patches to represent the ultrasound image and user-assisted initialization with labels, which acts as soft priors. The segmentation problem is formulated as a continuous minimum cut problem and solved with an efficient optimization algorithm. We validate our segmentation framework on clinical ultrasound imaging (prostate, fetus, and tumors of the liver and eye). We obtain high similarity agreement with the ground truth provided by medical expert delineations in all applications (94% DICE values in average) and the proposed algorithm performs favorably with the literature.

Phosphorylation regulates FOXC2-mediated transcription in lymphatic endothelial cells.

One of the key mechanisms linking cell signaling and control of gene expression is reversible phosphorylation of transcription factors. FOXC2 is a forkhead transcription factor that is mutated in the human vascular disease lymphedema-distichiasis and plays an essential role in lymphatic vascular development. However, the mechanisms regulating FOXC2 transcriptional activity are not well understood. We report here that FOXC2 is phosphorylated on eight evolutionarily conserved proline-directed serine/threonine residues. Loss of phosphorylation at these sites triggers substantial changes in the FOXC2 transcriptional program. Through genome-wide location analysis in lymphatic endothelial cells, we demonstrate that the changes are due to selective inhibition of FOXC2 recruitment to chromatin. The extent of the inhibition varied between individual binding sites, suggesting a novel rheostat-like mechanism by which expression of specific genes can be differentially regulated by FOXC2 phosphorylation. Furthermore, unlike the wild-type protein, the phosphorylation-deficient mutant of FOXC2 failed to induce vascular remodeling in vivo. Collectively, our results point to the pivotal role of phosphorylation in the regulation of FOXC2-mediated transcription in lymphatic endothelial cells and underscore the importance of FOXC2 phosphorylation in vascular development.

Characterization and clinical evaluation of CD10+ stroma cells in the breast cancer microenvironment.

PURPOSE: There is growing evidence that interaction between stromal and tumor cells is pivotal in breast cancer progression and response to therapy. Based on earlier research suggesting that during breast cancer progression, striking changes occur in CD10(+) stromal cells, we aimed to better characterize this cell population and its clinical relevance. EXPERIMENTAL DESIGN: We developed a CD10(+) stroma gene expression signature (using HG U133 Plus 2.0) on the basis of the comparison of CD10 cells isolated from tumoral (n = 28) and normal (n = 3) breast tissue. We further characterized the CD10(+) cells by coculture experiments of representative breast cancer cell lines with the different CD10(+) stromal cell types (fibroblasts, myoepithelial, and mesenchymal stem cells). We then evaluated its clinical relevance in terms of in situ to invasive progression, invasive breast cancer prognosis, and prediction of efficacy of chemotherapy using publicly available data sets. RESULTS: This 12-gene CD10(+) stroma signature includes, among others, genes involved in matrix remodeling (MMP11, MMP13, and COL10A1) and genes related to osteoblast differentiation (periostin). The coculture experiments showed that all 3 CD10(+) cell types contribute to the CD10(+) stroma signature, although mesenchymal stem cells have the highest CD10(+) stroma signature score. Of interest, this signature showed an important role in differentiating in situ from invasive breast cancer, in prognosis of the HER2(+) subpopulation of breast cancer only, and potentially in nonresponse to chemotherapy for those patients. CONCLUSIONS: Our results highlight the importance of CD10(+) cells in breast cancer prognosis and efficacy of chemotherapy, particularly within the HER2(+) breast cancer disease.