Second-trimester amniotic fluid proteins changes in subsequent spontaneous preterm birth

IntroductionThe global sequence of the pathogenesis of preterm labor remains unclear. This study aimed to compare amniotic fluid concentrations of extracellular matrix-related proteins (procollagen, osteopontin and IL-33), and of cytokines (IL-19, IL-6, IL-20, TNF alpha, TGF beta, and IL-1 beta) in asymptomatic women with and without subsequent spontaneous preterm delivery. Material and methodsWe used amniotic fluid samples of singleton pregnancy, collected by amniocentesis between 16 and 20 weeks' gestation, without stigmata of infection (i.e., all amniotic fluid samples were tested with broad-range 16 S rDNA PCR to distinguish samples with evidence of past bacterial infection from sterile ones), during a randomized, double-blind, placebo-controlled trial to perform a nested case-control laboratory study. Cases were women with a spontaneous delivery before 37 weeks of gestation (preterm group). Controls were women who gave birth at or after 39 weeks (full term group). Amniotic fluid concentrations of the extracellular matrix-related proteins and cytokines measured by immunoassays were compared for two study groups. : NCT00718705. ResultsBetween July 2008 and July 2011, in 12 maternal-fetal medicine centers in France, 166 women with available PCR-negative amniotic fluid samples were retained for the analysis. Concentrations of procollagen, osteopontin, IL-19, IL-6, IL-20, IL-33, TNF alpha, TGF beta, and IL-1 beta were compared between the 37 who gave birth preterm and the 129 women with full-term delivery. Amniotic fluid levels of procollagen, osteopontin, IL-19, IL-33, and TNF alpha were significantly higher in the preterm than the full-term group. IL-6, IL-20, TGF beta, and IL-1 beta levels did not differ between the groups. ConclusionsIn amniotic fluid 16 S rDNA PCR negative samples obtained during second-trimester amniocentesis, extracellular matrix-related protein concentrations (procollagen, osteopontin and IL-33), together with IL-19 and TNF alpha, were observed higher at this time in cases of later spontaneous preterm birth

Joint L1 − L2 Regularisation for Blind Speech Deconvolution. 18th Pacific-Rim Conference on Multimedia, Harbin, China, September 28-29, 2017

The purpose of blind speech deconvolution is to recover both the original speech source and the room impulse response (RIR) from the observed reverberant speech. This can be beneficial for speech intelligibility and speech perception. However, the problem is ill-posed, which often requires additional knowledge to solve. In order to address this problem, prior informations (such as the sparseness of signal or acoustic channel) are often exploited. In this paper, we propose a joint L1 − L2 regularisation based blind speech deconvolution method for a single-input and single-output (SISO) acoustic system with a high level of reverberation, where both the sparsity and density of the room impulse responses (RIR) are considered, by imposing an L1 and L2 norm constraint on their early and late part respectively. By employing an alternating strategy, both the source signal and early part in the RIR can be well reconstructed while the late part of the RIR can be suppressed

Ultrasound-induced Cavitation enhances the efficacy of Chemotherapy in a 3D Model of Pancreatic Ductal Adenocarcinoma with its microenvironment

Abstract Pancreatic ductal adenocarcinoma (PDAC) is supported by a complex microenvironment whose physical contribution to chemoresistance could be overcome by ultrasound (US) therapy. This study aims to investigate the ability of US-induced inertial cavitation in association with chemotherapy to alter tumor cell viability via microenvironment disruption. For this purpose, we used a 3D-coculture PDAC model partially mimicking the tumor and its microenvironment. Coculture spheroids combining DT66066 cells isolated from KPC-transgenic mice and murine embryonic fibroblasts (iMEF) were obtained by using a magnetic nanoshuttle method. Spheroids were exposed to US with incremental inertial cavitation indexes. Conditions studied included control, gemcitabine, US-cavitation and US-cavitation + gemcitabine. Spheroid viability was assessed by the reduction of resazurin and flow cytometry. The 3D-coculture spheroid model incorporated activated fibroblasts and produced type 1-collagen, thus providing a partial miniature representation of tumors with their microenvironment. Main findings were: (a) Gemcitabine (5 μM) was significantly less cytotoxic in the presence of KPC/iMEFs spheroids compared with KPC (fibroblast-free) spheroids; (b) US-induced inertial cavitation combined with Gemcitabine significantly decreased spheroid viability compared to Gemcitabine alone; (c) both cavitation and chemotherapy affected KPC cell viability but not that of fibroblasts, confirming the protective role of the latter vis-à-vis tumor cells. Gemcitabine toxicity is enhanced when cocultured spheroids of KPC and iMEF are exposed to US-cavitation. Although the model used is only a partial representation of PDAC, this experience supports the hypothesis that US-inertial cavitation can enhance drug penetration and cytotoxicity by disrupting PDAC microenvironment

Blind Speech Deconvolution via Pretrained Polynomial Dictionary and Sparse Representation. 18th Pacific-Rim Conference on Multimedia, Harbin, China, September 28-29, 2017

Blind speech deconvolution aims to estimate both the source speech and acoustic channel from the convolutive reverberant speech. The problem is ill-posed and underdetermined, which often requires prior knowledge for the estimation of the source and channel. In this paper, we propose a blind speech deconvolution method via a pretrained polynomial dictionary and sparse representation. A polynomial dictionary learning technique is employed to learn the dictionary from room impulse responses, which is then used as prior information to estimate the source and the acoustic impulse responses via an alternating optimization strategy. Simulations are provided to demonstrate the performance of the proposed method

Deep Convolutional Transform Learning

International audienceThis work introduces a new unsupervised representation learning technique called Deep Convolutional Transform Learning (DCTL). By stacking convolutional transforms, our approach is able to learn a set of independent kernels at different layers. The features extracted in an unsupervised manner can then be used to perform machine learning tasks, such as classification and clustering. The learning technique relies on a well-sounded alternating proximal minimization scheme with established convergence guarantees. Our experimental results show that the proposed DCTL technique outperforms its shallow version CTL, on several benchmark datasets

Macrophage Immune Memory Controls Endometriosis in Mice and Humans

International audienceEndometriosis is a frequent, chronic, inflammatory gynecological disease characterized by the presence of ectopic endometrial tissue causing pain and infertility. Macrophages have a central role in lesion establishment and maintenance by driving chronic inflammation and tissue remodeling. Macrophages can be reprogrammed to acquire memory-like characteristics after antigenic challenge to reinforce or inhibit a subsequent immune response, a phenomenon termed "trained immunity." Here, whereas bacille Calmette-Guérin (BCG) training enhances the lesion growth in a mice model of endometriosis, tolerization with repeated low doses of lipopolysaccharide (LPSlow) or adoptive transfer of LPSlow-tolerized macrophages elicits a suppressor effect. LPSlow-tolerized human macrophages mitigate the fibro-inflammatory phenotype of endometriotic cells in an interleukin-10 (IL-10)-dependent manner. A history of severe Gram-negative infection is associated with reduced infertility duration and alleviated symptoms, in contrast to patients with Gram-positive infection history. Thus, the manipulation of innate immune memory may be effective in dampening hyper-inflammatory conditions, opening the way to promising therapeutic approaches