Evaluation of mass spectrometric methods for detection of the anti-protozoal drug imidocarb

Imidocarb [N,N\u27-bis[3-(4,5-dihydro-1H-imidazol-2-yl)phenyl]urea, C19H20N6O1, m.w. 348.41] is a symmetrical carbanilide derivative used to treat disease caused by protozoans of the Babesia genus. Imidocarb, however, is also considered capable of suppressing Babesia-specific immune responses, allowing Babesia-positive horses to pass a complement fixation test (CFT) without eliminating the infection. This scenario could enable Babesia-infected horses to pass CFT-based importation tests. It is imperative to unequivocally identify and quantify equine tissue residues of imidocarb by mass spectrometry to address this issue. As a pretext to development of sensitive tissue assays, we have investigated possibilities of mass spectrometric (MS) detection of imidocarb. Our analyses disclosed that an unequivocal mass spectral analysis of imidocarb is challenging because of its rapid fragmentation under standard gas chromatography (GC)-MS conditions. In contrast, solution chemistry of imidocarb is more stable but involves distribution into mono- and dicationic species, m/z 349 and 175, respectively, in acid owing to the compound\u27s inherent symmetrical nature. Dicationic imidocarb was the preferred complex as viewed by either direct infusion-electrospray-MS or by liquid chromatography (LC)-MS. Dicationic imidocarb multiple reaction monitoring (MRM: m/z 175 → 162, 145, and 188) therefore offer the greatest opportunities for sensitive detection and LC-MS is more likely than GC-MS to yield a useful quantitative forensic analytical method for detecting imidocarb in horses

Engaging Children to Co-create Outdoor Play Activities for Place-making

Outdoor play activities are one of the ways via which children can acquire a sense of place towards their neighbourhood. Engaging children in the design of these activities through Participatory Design (PD) holds promise. However, knowledge lacks on the characteristics of place-making processes for children, the changing dynamics in these processes, and how PD can contribute to this. This paper proposes a PD method, grounded in literature, to support children in co-creating outdoor play activities for place-making. The method is applied with 42 children in Rotterdam. Involvementof local partners, preparation meetings, and PD materials tailored to children’s interests and skills are vital to enable children to design outdoor play activities that are meaningful to them.System Engineerin

Ramucirumab and Docetaxel in Patients with Metastatic Urothelial Carcinoma Harboring Fibroblast Growth Factor Receptor Alterations: A Case Series and Literature Review

Metastatic urothelial carcinoma (mUC) has a poor prognosis with a 5-year survival probability of 4.8%. The mainstay of first-line treatment is platinum-based chemotherapy. Second-line therapy involves immune checkpoint inhibitors or a fibroblast growth factor receptor (FGFR) inhibitor, erdafitinib, for patients harboring selected FGFR alterations. Several additional agents are under development for the treatment of mUC. Recent studies demonstrate that ramucirumab and docetaxel have clinical activity in mUC. We report two patients with metastatic upper tract urothelial cancer (mUTUC) with FGFR alterations who were heavily pretreated with FGFR inhibitors that later showed response to ramucirumab and docetaxel. Preclinical studies indicate that FGF and VEGF pathways work synergistically, which could explain the observations in our patients. Our findings may represent another treatment option for patients with mUC and FGFR alterations who have progressed on multiple lines of therapy

Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications

Automated detection of sclerotic metastases (bone lesions) in Computed Tomography (CT) images has potential to be an important tool in clinical practice and research. State-of-the-art methods show performance of 79 % sensitivity or truepositive (TP) rate, at 10 false-positives (FP) per volume. We design a two-tiered coarse-to-fine cascade framework to first operate a highly sensitive candidate generation system at a maximum sensitivity of ∼92% but with high FP level (∼50 per patient). Regions of interest (ROI) for lesion candidates are generated in this step and function as input for the second tier. In the second tier we generate N 2D views, via scale, random translations, and rotations with respect to each ROI centroid coordinates. These random views are used to train a deep Convolutional Neural Network (CNN) classifier. In testing, the CNN is employed to assign individual probabilities for a new set of N random views that are averaged at each ROI to compute a final per-candidate classification probability. This second tier behaves as a highly selective process to reject difficult false positives while preserving high sensitivities. We validate the approach on CT images of 59 patients (49 with sclerotic metastases and 10 normal controls). The proposed method reduces the number of FP/vol.from 4 to 1.2, 7 to 3, and 12 to 9.5 when comparing a sensitivity rates of 60, 70, and 80% respectively in testing. The Area-Under-the-Curve (AUC) is 0.834. The results show marked improvement upon previous work