Interspecies comparison of the early transcriptomic changes associated with hepatitis B virus exposure in human and macaque immune cell populations.

Background and aims: Hepatitis B virus (HBV) infection affects 300 million individuals worldwide, representing a major factor for the development of hepatic complications. Although existing antivirals are effective in suppressing replication, eradication of HBV is not achieved. Therefore, a multi-faceted approach involving antivirals and immunomodulatory agents is required. Non-human primates are widely used in pre-clinical studies due to their close evolutionary relationship to humans. Nonetheless, it is fundamental to identify the differences in immune response between humans and these models. Thus, we performed a transcriptomic characterization and interspecies comparison of the early immune responses to HBV in human and cynomolgus macaques. Methods: We characterized early transcriptomic changes in human and cynomolgus B cells, T cells, myeloid and plasmacytoid dendritic cells (pDC) exposed to HBV ex vivo for 2 hours. Differentially-expressed genes were further compared to the profiles of HBV-infected patients using publicly-available single-cell data. Results: HBV induced a wide variety of transcriptional changes in all cell types, with common genes between species representing only a small proportion. In particular, interferon gamma signaling was repressed in human pDCs. At the gene level, interferon gamma inducible protein 16 (IFI16) was upregulated in macaque pDCs, while downregulated in humans. Moreover, IFI16 expression in pDCs from chronic HBV-infected patients anti-paralleled serum HBsAg levels. Conclusion: Our characterization of early transcriptomic changes induced by HBV in humans and cynomolgus macaques represents a useful resource for the identification of shared and divergent host responses, as well as potential immune targets against HBV.

Secrecy Coding Analysis of Short-Packet Full-Duplex Transmissions with Joint Iterative Channel Estimation and Decoding Processes.

This paper studies the secrecy coding analysis achieved by the self-jamming technique in the presence of an eavesdropper by considering a short-packet Full-Duplex (FD) transmission developed based on iterative blind or semi-blind channel estimation and advanced decoding algorithms. Indeed, the legitimate receiver and eavesdropper can simultaneously receive the intended signal from the transmitter and broadcast a self-jamming or jamming signal to the others. Unlike other conventional techniques without feedback, the blind or semi-blind algorithm applied at the legitimate receiver can simultaneously estimate, firstly, the Self-Interference (SI) channel to cancel the SI component and, secondly, estimate the propagation channel, then decode the intended messages by using 5G Quasi-Cyclic Low-Density Parity Check (QC-LDPC) codes. Taking into account the passive eavesdropper case, the blind channel estimation with a feedback scheme is applied, where the temporary estimation of the intended channel and the decoded message are fed back to improve both the channel estimation and the decoding processes. Only the blind algorithm needs to be implemented in the case of a passive eavesdropper because it achieves sufficient performances and does not require adding pilot symbols as the semi-blind algorithm. In the case of an active eavesdropper, based on its robustness in the low region of the Signal-to-Noise Ratio (SNR), the semi-blind algorithm is considered by trading four pilot symbols and only requiring the feedback for channel estimation processes in order to overcome the increase in noise in the legitimate receiver. The results show that the blind or semi-blind algorithms outperform the conventional algorithm in terms of Mean Square Error (MSE), Bit Error Rate (BER) and security gap (Sg). In addition, it has been shown that the blind or semi-blind algorithms are less sensitive to high SI and self-jamming interference power levels imposed by secured FD transmission than the conventional algorithms without feedback.

Joint Semi-Blind Self-Interference Cancellation and Equalisation Processes in 5G QC-LDPC-Encoded Short-Packet Full-Duplex Transmissions.

The paper proposes a joint semi-blind algorithm for simultaneously cancelling the self-interference component and estimating the propagation channel in 5G Quasi-Cyclic Low-Density Parity-Check (QC-LDPC)-encoded short-packet Full-Duplex (FD) transmissions. To avoid the effect of channel estimation processes when using short-packet transmissions, this semi-blind algorithm was developed by taking into account only a small number (four at least) pilot symbols, which was integrated with the intended information sequence and used for the feedback loop of the estimation of the channels. The results showed that this semi-blind algorithm not only achieved nearly optimal performance, but also significantly reduced the processing time and computational complexity. This semi-blind algorithm can also improve the performances of the Mean-Squared Error (MSE) and Bit Error Rate (BER). The results of this study highlight the potential efficiency of this joint semi-blind iterative algorithm for 5G and Beyond and/or practical IoT transmission scenarios.