Phosphate dynamics in an urban sewer: A case study of Nancy, France

International audienceThe nature of phosphate phases present in suspended matter, biofilm, and sediment of Greater Nancy sewer system, was investigated over a period of two years. The phosphate speciation was determined by two approaches: a direct identification of phosphorus mineral phases was conducted by Transmission Electron Microscopy (TEM) coupled with Energy Dispersive X-ray Spectroscopy (EDXS), whereas a chemical extraction of samples provided an estimate of phosphorus pools defined by the fractionation scheme. Quantitative analysis of 1340 individual particles allowed to draw a picture of phosphate species distributions along the sewer system and over time. Amorphous Ca-phosphates (brushite, whitlockite, octacalcium phosphate, Mg-brushite, hydroxyapatite and carbapatite) are ubiquitous although brushite dominated upstream, and octacalcium phosphate and apatite prevailed downstream and in sediments. Al-Ca-phosphate minerals such as foggite, bearthite, gatumbaite, and crandallite appeared downstream and in biofilms. Changes in Ca-phosphate phase distribution were related to phase transformations from brushite to hydroxyapatite that were shown to be kinetically driven. The restriction of Al-Ca-phosphates to downstream of the sewer system was most probably related to the lower pHs measured at these sites. The pH dependency was confirmed by stability calculations. TEM examination of chemical extraction residues revealed the presence of neoformed Al-Ca-phosphate species that invalidate the fractionation scheme. On the other hand, it confirmed that phosphate phases may undergo significant geochemical changes over a short time scale

Humoral Response Induced by Prime-Boost Vaccination with the ChAdOx1 nCoV-19 and mRNA BNT162b2 Vaccines in a Teriflunomide-Treated Multiple Sclerosis Patient.

Patients with multiple sclerosis (MS) are treated with drugs that may impact immune responses to SARS-CoV-2 vaccination. Evaluation of "prime-boost" (heterologous) vaccination regimens including a first administration of a viral vector-based vaccine and a second one of an mRNA-based vaccine in such patients has not yet been completed. Here, we present the anti-spike protein S humoral response, including the neutralizing antibody response, in a 54-year-old MS patient who had been treated with teriflunomide for the past 2 years and who received a heterologous ChAdOx1 nCoV-19/ BNT162b2 vaccination regimen. The results showed a very strong anti-S IgG response and a good neutralizing antibody response. These results show that teriflunomide did not prevent the development of a satisfactory humoral response in this MS patient after vaccination with a ChAdOx1 nCoV-19/ BNT162b2 prime-boost protocol

Atlas-based segmentation of medical images locally constrained by level sets

Atlas-based segmentation has become a standard paradigm for exploiting prior knowledge in medical image segmentation. In this paper, we propose a method to exploit both the robustness of global registration techniques and the accuracy of a local registration based on level set tracking. First, the atlas is globally put in correspondence with the patient image by an affine and an intensity-based non rigid registration. Based on this rough initialisation, the level set functions corresponding to particular objects of interest of the deformed atlas are used to segment the corresponding objects in the patient image. We propose a technique to derive a dense deformation field from the motion of these level set functions. This is particularly important when we want to infer the position of invisible structures like the brain sub-thalamic nuclei from the position of visible surrounding structures. This can also be advantageously exploited to register an atlas following a hierarchical approach. Results are shown on 2D synthetic images and 2D real images extracted from brain and prostate MR volumes and neck CT volumes

Statistical Model of Shape Moments with Active Contour Evolution for Shape Detection and Segmentation

This paper describes a novel method for shape representation and robust image segmentation. The proposed method combines two well known methodologies, namely, statistical shape models and active contours implemented in level set framework. The shape detection is achieved by maximizing a posterior function that consists of a prior shape probability model and image likelihood function conditioned on shapes. The statistical shape model is built as a result of a learning process based on nonparametric probability estimation in a PCA reduced feature space formed by the Legendre moments of training silhouette images. A greedy strategy is applied to optimize the proposed cost function by iteratively evolving an implicit active contour in the image space and subsequent constrained optimization of the evolved shape in the reduced shape feature space. Experimental results presented in the paper demonstrate that the proposed method, contrary to many other active contour segmentation methods, is highly resilient to severe random and structural noise that could be present in the data

AlloHSCT for inv(3)(q21;q26)/t(3;3)(q21;q26) AML : a report from the acute leukemia working party of the European society for blood and marrow transplantation

Acute myeloid leukemia with inv(3)(q21;q26.2)/t(3;3)(q21;q26.2) (3q26 AML) is a rare disease with poor prognosis and median survival ofPeer reviewe

Protein mimetic amyloid inhibitor potently abrogates cancer-associated mutant p53 aggregation and restores tumor suppressor function

Missense mutations in p53 are severely deleterious and occur in over 50% of all human cancers. The majority of these mutations are located in the inherently unstable DNA-binding domain (DBD), many of which destabilize the domain further and expose its aggregation-prone hydrophobic core, prompting self-assembly of mutant p53 into inactive cytosolic amyloid-like aggregates. Screening an oligopyridylamide library, previously shown to inhibit amyloid formation associated with Alzheimer\u2019s disease and type II diabetes, identified a tripyridylamide, ADH-6, that abrogates self-assembly of the aggregation-nucleating subdomain of mutant p53 DBD. Moreover, ADH-6 targets and dissociates mutant p53 aggregates in human cancer cells, which restores p53\u2019s transcriptional activity, leading to cell cycle arrest and apoptosis. Notably, ADH-6 treatment effectively shrinks xenografts harboring mutant p53, while exhibiting no toxicity to healthy tissue, thereby substantially prolonging survival. This study demonstrates the successful application of a bona fide small-molecule amyloid inhibitor as a potent\ua0anticancer agent

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

Verification and Compliance in Collaborative Processes

Evidently, COVID-19 has changed our lives and is likely to make a lasting impact on our economic development and our industry and services. With the ongoing process of digital transformation in industry and services, Collaborative Networks (CNs) is required to be more efficient, productive, flexible, resilient and sustainable according to change of situations and related rules applied afterwards. Although the CN area is relatively young, it requires the previous research to be extended, i.e. business process management from dealing with processes within a single organization into processes across different organizations. In this paper, we review current business process verification and compliance research. Different tools approaches and limitations of them are compared. The further research issues and potential solutions of business process verification and compliance check are discussed in the context of CNs

Inborn errors of OAS-RNase L in SARS-CoV-2-related multisystem inflammatory syndrome in children

Multisystem inflammatory syndrome in children (MIS-C) is a rare and severe condition that follows benign COVID-19. We report autosomal recessive deficiencies of OAS1, OAS2, or RNASEL in five unrelated children with MIS-C. The cytosolic double-stranded RNA (dsRNA)-sensing OAS1 and OAS2 generate 2'-5'-linked oligoadenylates (2-5A) that activate the single-stranded RNA-degrading ribonuclease L (RNase L). Monocytic cell lines and primary myeloid cells with OAS1, OAS2, or RNase L deficiencies produce excessive amounts of inflammatory cytokines upon dsRNA or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) stimulation. Exogenous 2-5A suppresses cytokine production in OAS1-deficient but not RNase L-deficient cells. Cytokine production in RNase L-deficient cells is impaired by MDA5 or RIG-I deficiency and abolished by mitochondrial antiviral-signaling protein (MAVS) deficiency. Recessive OAS-RNase L deficiencies in these patients unleash the production of SARS-CoV-2-triggered, MAVS-mediated inflammatory cytokines by mononuclear phagocytes, thereby underlying MIS-C