ER intrabody-vermittelter Knockdown im Zebrafish

Gene knockout and knockdown approaches have been extensively used in zebrafish to study genes playing a pivotal role during the development, or to create animal models of human diseases. In the past ten years, evidence has accumulated that using different loss-of-function methods, acting at DNA or RNA level to interfere with the expression of a specific gene may often result in the generation of completely independent phenotypes. Genetic compensation on one side and off-targeting effects on the other have been identified as main contributors to this phenomenon. The ER intrabody knockdown approach, acting at protein level with high specificity, is intrinsically less prone to such drawbacks, and additionally offers a higher level of protein isoform discrimination. In this study, we describe the process of antibody validation for highly specific protein identification in different assays and for targeted protein knockdown in vitro and in vivo of zebrafish Cadherin-2 (Cdh2). We have generated 11 novel sequence-defined human scFv antibodies against zebrafish Cdh2 via phage display. Cdh2 parachute mutant and Cdh2-GFP transgenic lines were used to compare antibody specificity in immunofluorescent staining and flow cytometry analysis, as well as whole mount immunohistochemistry. Four of these recombinant monoclonal antibodies showed drastically improved specificity against zCdh2 compared to the only commercial available reagent, which was found highly cross-reactive towards zCdh2-- cells, independently from the type of sample preparation. Further, we generated ER intrabodies to zCdh2 via genetically fusing the newly generated scFv antibody genes to the DNA encoding for the ER localization KDEL peptide. We evaluated ER intrabodies‘ capability to mediate zCdh2 knockdown from the surface of PAC2 cells and to induce target antigen degradation. In vivo, the ER intrabody SH1352-D7-KDEL expressed in atoh1a+ progenitors of zebrafish embryos was shown to interfere with tegmental hindbrain nuclei primordia formation. Our validated protein knockdown approach constitutes an expansion of the available zebrafish tool box for gene function studies and for modeling human diseases in this organism model. We indirectly proved that protein based approaches can have a beneficial impact on the zebrafish community, provided that the process of generation of these tools is subjected to an extensive and thoughtful characterization processes.Gen-Knockout- und Knockdown-Ansätze werden in Zebrafischen umfassend eingesetzt, um Gene zu untersuchen, die während der Entwicklung eine zentrale Rolle spielen, oder um Tiermodelle für menschliche Krankheiten zu erstellen. In den letzten zehn Jahren hat sich gezeigt, dass die Verwendung verschiedener Funktionsverlustmethoden, die auf DNA- oder RNA-Ebene wirken, um die Expression eines bestimmten Gens zu stören, oft zur Erzeugung völlig unabhängiger Phänotypen führen kann. Genetische Kompensation einerseits und Off-Targeting-Effekte andererseits wurden als Hauptursachen für dieses Phänomen identifiziert. Der ER Intrabody Knockdown-Ansatz, der auf Proteinebene mit hoher Spezifität agiert, ist an sich weniger anfällig für solche Nachteile und bietet zusätzlich eine höhere Ebene des Unterscheidungspotenzials bei Proteinisoformen. In dieser Studie beschreiben wir den Prozess der Antikörpervalidierung zur hochspezifischen Proteinidentifikation in verschiedenen Assays und zum gezielten Proteinabbau in vitro und in vivo von Zebrafisch Cadherin-2 (Cdh2). Wir haben 11 neuartige, sequenzdefinierte humane scFv-Antikörper gegen Zebrafisch Cdh2 mittels Phagen-Display generiert. Transgene Linien mit einer Cdh2 Parachute-Mutante bzw. Cdh2-GFP wurden verwendet, um die Antikörperspezifitäten in der immunfluoreszierenden Färbe- und Durchflusszytometrieanalyse, und der Immunhistochemie von whole-mount-Montagen zu vergleichen. Vier unserer rekombinanten monoklonalen Antikörper zeigten eine deutlich verbesserte Spezifität gegen zCdh2 im Vergleich zu dem einzigen kommerziell erhältlichen Reagenz, das unabhängig von der Art der Probenvorbereitung eine hohe Kreuzreaktivität gegenüber zCdh2---Zellen zeigte. Außerdem generierten wir ER-Intrakörper gegen zCdh2 durch genetische Fusion der neu generierten scFv-Antikörpergene mit DNA, die für das ER-Lokalisierungs-Peptid KDEL kodiert. Wir untersuchten die Fähigkeit dieser Antikörper, den zCdh2-Knockdown von der Oberfläche der PAC2-Zellen zu vermitteln und den Abbau des Antigens zu induzieren. In vivo konnte gezeigt werden, dass der ER-Intrakörper SH1352-D7-KDEL, der in atoh1a+-Vorläufern von Zebrafischembryonen exprimiert wurde, die Bildung tegmenteller Hinterhirnkerne nuclei primordia stört. Unser validierter Protein-Knockdown-Ansatz stellt eine Erweiterung der verfügbaren Zebrafisch-Toolbox für Genfunktionsstudien und zur Modellierung menschlicher Krankheiten in diesem Organismusmodell dar. Wir haben indirekt bewiesen, dass proteinbasierte Ansätze einen positiven Einfluss auf die Zebrafisch-Forschungsgemeinschaft haben können, vorausgesetzt, dass der Prozess der Generierung dieser Werkzeuge einem umfangreichen und durchdachten Charakterisierungsprozess unterzogen wird

Chapter L’Urbano. Origine e fortuna di una novella pseudo-boccaccesca

The paper pursues an investigation on an apocryphal text still underinvestigated by scholars: the Urbano, falsely attributed to Boccaccio. The first part focuses on its fortune in the Boccaccio’s canon, from the first edition of the Vocabolario della Crusca to the Boccaccio’s complete works edited in the Ottocento; furthermore, are pointed out its connections with the Libellus de Constantino Magno eiusque matre Helena, the main source of the plot, and with other genealogical medieval tales, such as the Libro imperiale and the Manfredo. The second part focuses on the manuscript tradition of the text, in order to demonstrate as its circulation in Quattrocento’s miscellaneous manuscripts of rhetorical texts in the vernacular, containing several texts by Boccaccio, has probably influenced the spurious attribution

GCNH: A Simple Method For Representation Learning On Heterophilous Graphs

Graph Neural Networks (GNNs) are well-suited for learning on homophilous graphs, i.e., graphs in which edges tend to connect nodes of the same type. Yet, achievement of consistent GNN performance on heterophilous graphs remains an open research problem. Recent works have proposed extensions to standard GNN architectures to improve performance on heterophilous graphs, trading off model simplicity for prediction accuracy. However, these models fail to capture basic graph properties, such as neighborhood label distribution, which are fundamental for learning. In this work, we propose GCN for Heterophily (GCNH), a simple yet effective GNN architecture applicable to both heterophilous and homophilous scenarios. GCNH learns and combines separate representations for a node and its neighbors, using one learned importance coefficient per layer to balance the contributions of center nodes and neighborhoods. We conduct extensive experiments on eight real-world graphs and a set of synthetic graphs with varying degrees of heterophily to demonstrate how the design choices for GCNH lead to a sizable improvement over a vanilla GCN. Moreover, GCNH outperforms state-of-the-art models of much higher complexity on four out of eight benchmarks, while producing comparable results on the remaining datasets. Finally, we discuss and analyze the lower complexity of GCNH, which results in fewer trainable parameters and faster training times than other methods, and show how GCNH mitigates the oversmoothing problem.Comment: Accepted at 2023 International Joint Conference on Neural Networks (IJCNN

2-hop Neighbor Class Similarity (2NCS): A graph structural metric indicative of graph neural network performance

Graph Neural Networks (GNNs) achieve state-of-the-art performance on graph-structured data across numerous domains. Their underlying ability to represent nodes as summaries of their vicinities has proven effective for homophilous graphs in particular, in which same-type nodes tend to connect. On heterophilous graphs, in which different-type nodes are likely connected, GNNs perform less consistently, as neighborhood information might be less representative or even misleading. On the other hand, GNN performance is not inferior on all heterophilous graphs, and there is a lack of understanding of what other graph properties affect GNN performance. In this work, we highlight the limitations of the widely used homophily ratio and the recent Cross-Class Neighborhood Similarity (CCNS) metric in estimating GNN performance. To overcome these limitations, we introduce 2-hop Neighbor Class Similarity (2NCS), a new quantitative graph structural property that correlates with GNN performance more strongly and consistently than alternative metrics. 2NCS considers two-hop neighborhoods as a theoretically derived consequence of the two-step label propagation process governing GCN's training-inference process. Experiments on one synthetic and eight real-world graph datasets confirm consistent improvements over existing metrics in estimating the accuracy of GCN- and GAT-based architectures on the node classification task.Comment: Accepted at the 3rd Workshop on Graphs and more Complex structures for Learning and Reasoning (GCLR) at AAAI 202

The invisible businessman: Nuclear physics, patenting practices,and trading activities in the 1930s

In the 1930s the production of patents for the protection of intellectual rights became central to the research activities of Enrico Fermi and his group, consistently with a research policy emerging within the Italian Fascist Regime. Behind their work was an international network consisting of businessmen, industrialists, and multinationals who helped them patent their method for the production of artificial radioactive elements and to promote its industrial exploitation. The lack of research funding combined with a more aggressive foreign policy of the regime made it impossible for the group to continue these activities in Rome, and in 1938 the promulgation of racial laws forced them to migrate abroad

On Type II strings in exact superconformal non-constant RR backgrounds

An explicitly exact superconformal description is provided to some classes of Type II string theories in non constant RR backgrounds. This is done by applying the manifest (2,2) approach of Berkovits and Maldacena to Type II strings and by studying the condition of exact conformal invariance of certain supersymmetric backgrounds. We find a new set of exact type IIA strings with non constant RR 2-form and 4-form curvatures and for type IIB with non constant 3-form curvature.Comment: 15 pages; typos and a reference adde

Intra- and inter-operator reliability assessment of a novel extramedullary accelerometer-based smart cutting guide for total knee arthroplasty: an in vivo study

Purpose The purpose is to verify the intra- and inter-operator reliability of an extramedullary (EM) accelerometer-based smart cutting guide for distal femoral resection during primary total knee arthroplasty (TKA). The hypothesis of the present study was that the use of the device would result in a good correlation between different operators with a difference between repeated measurements of less than 1 degrees.Methods Twenty-five not consecutive patients with knee osteoarthritis undergone to primary TKA using an EM inertial-based cutting guide to perform distal femoral resection. In order to assess the agreement in femoral axis definition of the device, two operators performed three time each the manoeuvres necessary to define axis. Inter-rater agreement was evaluated with Bland and Altman agreement test. Intra-rater repeatability was evaluated analysing average results distribution of repeated measurements. Accuracy of the device was evaluated comparing differences between intra-operative device data with final implant alignment measured on post-operative longstanding x-rays using Students' t test.Results Agreement between the two operators was statistically significant (p < 0.05) with a bias of - 0.4 degrees (95% CI -0.6 degrees to - 0.2 degrees). Average difference between cut orientation measured with device and final implant position, measured on x-rays, was 0.2 degrees (95% CI - 1.5 degrees to 1.7 degrees) with no statistical difference between the two measurements. Final implant alignment, measured on x-ray, was 90.2 degrees, with 95% of cases distributed within range 88.0 degrees to 92.0 degrees for varus-valgus and 2.8 degrees and with 95% of cases distributed within range 2.0 degrees to 4.0 degrees for flexion-extension.Conclusions The EM accelerometer-based smart cutting guide used to perform distal femoral resection during primary TKA demonstrated a good intra- and inter-operator reliability in the present in vivo study