Structural analysis of the adenovirus type 2 E3/19K protein using mutagenesis and a panel of conformation-sensitive monoclonal antibodies

The E3/19K protein of human adenovirus type 2 (Ad2) was the first viral protein shown to interfere with antigen presentation. This 25 kDa transmembrane glycoprotein binds to major histocompatibility complex (MHC) class I molecules in the endoplasmic reticulum (ER), thereby preventing transport of newly synthesized peptide–MHC complexes to the cell surface and consequently T cell recognition. Recent data suggest that E3/19K also sequesters MHC class I like ligands intracellularly to suppress natural killer (NK) cell recognition. While the mechanism of ER retention is well understood, the structure of E3/19K remains elusive. To further dissect the structural and antigenic topography of E3/19K we carried out site-directed mutagenesis and raised monoclonal antibodies (mAbs) against a recombinant version of Ad2 E3/19K comprising the lumenal domain followed by a C-terminal histidine tag. Using peptide scanning, the epitopes of three mAbs were mapped to different regions of the lumenal domain, comprising amino acids 3–13, 15–21 and 41–45, respectively. Interestingly, mAb 3F4 reacted only weakly with wild-type E3/19K, but showed drastically increased binding to mutant E3/19K molecules, e.g. those with disrupted disulfide bonds, suggesting that 3F4 can sense unfolding of the protein. MAb 10A2 binds to an epitope apparently buried within E3/19K while that of 3A9 is exposed. Secondary structure prediction suggests that the lumenal domain contains six β-strands and an α-helix adjacent to the transmembrane domain. Interestingly, all mAbs bind to non-structured loops. Using a large panel of E3/19K mutants the structural alterations of the mutations were determined. With this knowledge the panel of mAbs will be valuable tools to further dissect structure/function relationships of E3/19K regarding down regulation of MHC class I and MHC class I like molecules and its effect on both T cell and NK cell recognition

Roadmap on data-centric materials science

Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research

A distributed space-time trellis coding approach for multi-terminal relay networks

Cooperative relaying is a promising alternative for conventional mobile communications systems as it is able to increase coverage and throughput of these systems. Due to practical constraints most cooperative relaying protocols employ half-duplex relays which implies the need for an increased data rate on the individual links and causes a significant performance loss at higher rates. This paper presents a novel cooperative relaying approach exploiting existing large scale space diversity as well as an additional coding gain by employing a spatial duplex approach. The scheme utilizes a network of alternatingly sending and receiving relay terminals where only one relay node is transmitting at a particular time. This spatial duplexing approach is used to implement a distributed Space-Time Trellis Code (STTC) for virtual antenna arrays. In this work, the protocol is applied to a convolutionally coded system. Due to the serial concatenation of an inner STTC and an outer convolutional code, the destination is able to use well-known turbo-decoding algorithms to reduce the frame error rate of the system. The assessment of the approach is done by comparing it with conventional relaying, a time/frequency duplex cooperative relaying protocol and direct transmission

Protocols For Half-Duplex Multiple Relay Networks

In this paper we present several strategies for multiple relay networks which are constrained by a half-duplex operation, i. e., each node either transmits or receives on a particular resource. Using the discrete memoryless multiple relay channel we present achievable rates for a multilevel partial decode-and-forward approach which generalizes previous results presented by Kramer and Khojastepour et al.. Furthermore, we derive a compress-and-forward approach using a regular encoding scheme which simplifies the encoding and decoding procedure and improves the achievable rates in general. Finally, we give achievable rates for a mixed strategy used in a fourterminal network with alternately transmitting relay nodes

A Generalized Mixed Strategy for Multiterminal Relay Networks

In their fundamental paper, Cover and El Gamal presented three basic coding strategies – decode-and-forward, compress-and-forward and a mixed strategy based on partial decode-and-forward and compress-and-forward – which are still the basis for many recent relaying protocols. So far, only parts of their work are applied to networks of relay nodes, e. g., the decode-and-forward as well as compress-and-forward approach. This work generalizes a mixed approach of partial decode-andforward and compress-and-forward to networks of relay nodes. We further highlight how the “successive refinement problem” and the “broadcast channel problem with degraded message sets” are applied in our approach. Finally, we formulate achievable rates for the discrete memoryless relay channel consisting of two relay nodes