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Respiratory Virus-Specific and Time-Dependent Interference of Adenovirus Type 2, SARS-CoV-2 and Influenza Virus H1N1pdm09 During Viral Dual Co-Infection and Superinfection In Vitro.
Viruses
December 2024
Department of Experimental and Clinical Medicine, University of Florence, Viale Morgagni 48, I-50134 Florence, Italy.
Background: Understanding the interference patterns of respiratory viruses could be important for shedding light on potential strategies to combat these human infectious agents.
Objective: To investigate the possible interactions between adenovirus type 2 (AdV2), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A/H1N1 pandemic (H1N1pdm09) using the A549 cell line.
Methods: Single infections, co-infections, and superinfections (at 3 and 24 h after the first virus infection) were performed by varying the multiplicity of infection (MOI).
Characterization of Hepatitis B Virus Transcripts in Chronically HBV-Infected Chimpanzees and Patients Treated with ARC-520 siRNA Demonstrates Transcriptional Silencing of cccDNA.
Viruses
December 2024
Department of Medicine & State Key Laboratory of Liver Research, School of Clinical Medicine, The University of Hong Kong, Hong Kong, China.
Full-length hepatitis B virus (HBV) transcripts of chimpanzees and patients treated with multidose (MD) HBV siRNA ARC-520 and entecavir (ETV) were characterized by single-molecule real-time (SMRT) sequencing, identifying multiple types of transcripts with the potential to encode HBx, HBsAg, HBeAg, core, and polymerase, as well as transcripts likely to be derived from dimers of dslDNA, and these differed between HBeAg-positive (HBeAg+) and HBeAg-negative (HBeAg-) individuals. HBV transcripts from the last follow-up ~30 months post-ARC-520 treatment were categorized from one HBeAg+ (one of two previously highly viremic patients that became HBeAg- upon treatment and had greatly reduced cccDNA products) and four HBeAg- patients. The previously HBeAg+ patient received a biopsy that revealed that he had 3.
View Article and Find Full Text PDFExpression of an Efficient Selection Marker Out of a Duplicated Site in the ITRs of a Modified Vaccinia Virus Ankara (MVA).
Vaccines (Basel)
December 2024
ProBioGen AG, 13086 Berlin, Germany.
: Poxviruses are large DNA viruses that replicate in the host cytoplasm without a nuclear phase. As vaccine vectors, they can package and express large recombinant cassettes from different positions of their genomic core region. We present a comparison between wildtype modified vaccinia Ankara (MVA) and isolate CR19, which has significantly expanded inverted terminal repeats (ITRs).
View Article and Find Full Text PDFEnergy-Efficient Dynamic Enhanced Inter-Cell Interference Coordination Scheme Based on Deep Reinforcement Learning in H-CRAN.
Sensors (Basel)
December 2024
College of AI/SW Convergence, Kyungnam University, 7 Gyeongnamdaehak-ro, Masanhappo-gu, Changwon 51767, Republic of Korea.
The proliferation of 5G networks has revolutionized wireless communication by delivering enhanced speeds, ultra-low latency, and widespread connectivity. However, in heterogeneous cloud radio access networks (H-CRAN), efficiently managing inter-cell interference while ensuring energy conservation remains a critical challenge. This paper presents a novel energy-efficient, dynamic enhanced inter-cell interference coordination (eICIC) scheme based on deep reinforcement learning (DRL).
View Article and Find Full Text PDFOptimization of Imaging Reconnaissance Systems Using Super-Resolution: Efficiency Analysis in Interference Conditions.
Sensors (Basel)
December 2024
Institute of Communication Systems, Faculty of Electronics, Military University of Technology, 00-908 Warsaw, Poland.
Image reconnaissance systems are critical in modern applications, where the ability to accurately detect and identify objects is crucial. However, distortions in real-world operational conditions, such as motion blur, noise, and compression artifacts, often degrade image quality, affecting the performance of detection systems. This study analyzed the impact of super-resolution (SR) technology, in particular, the Real-ESRGAN model, on the performance of a detection model under disturbed conditions.
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