Background: One of the major characteristics of the human immunodeficiency virus type 1 (HIV-1) is its unusually high degree of genetic variability, which involves in genetic diagnosis, subtyping, vaccine design, and epidemiology. HIV-1 CRF01_AE is a main prevalent HIV-1 recombinant strain in China. In this study, three full-length CRF01_AE genomes from Fujian Province, China were cloned, sequenced, and analyzed; and the further genetic diversity defining and epidemiologic analysis were carried out.
Methods: Proviral DNA was extracted from non-cultured peripheral blood mononuclear cells, the near full-length HIV-1 genome was amplified and the PCR products were cloned into pCR-XL-TOPO vector and sequenced. 5'-long terminal repeat (LTR) and 3'-LTRs were amplified by additional independent PCR and cloned into pMD18T vector. Gene-based phylogenic tree was constructed and genetic distances were calculated by MEGA 3.1. Simplot was used for Bootscan analysis.
Results: The phylogeny and genetic distance analysis of the three near full-length sequences confirmed that these three samples clustered with CRF01_AE isolates, more close to Thailand CRF01_AE strain CM240, and were distantly related to African CRF01_AE strain 90CF402. Analysis of their genomic organization revealed the presence of nine potential open reading frames. There were no major deletions, rearrangements, or insertions in the three sequences, but an in-frame stop codon was found in tat gene of Fj051. LTRs of the three sequences contained a few nucleotides mutation. We did not find new mosaic recombinant in the three sequences. The V3 motif was GPGQ in all the three sequences, and there were only few amino acids differences in all three V3 loop sequences.
Conclusion: This report reveals the background of the three full-length CRF01_AE genomes, the most dominantly circulating HIV-1 strain in Fujian Province, China. The work is essential for the design and development of an effective AIDS vaccine for the region.
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Viruses
December 2024
Foundation Plant Services, University of California-Davis, Davis, CA 95616, USA.
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Key Laboratory of Green Prevention and Control of Tropical Plant Diseases and Pests (Ministry of Education), School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China.
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Department of Computer Engineering, Gachon University, Sujeong-gu, Seongnam-si 13120, Republic of Korea.
Generating accurate and contextually rich captions for images and videos is essential for various applications, from assistive technology to content recommendation. However, challenges such as maintaining temporal coherence in videos, reducing noise in large-scale datasets, and enabling real-time captioning remain significant. We introduce MIRA-CAP (Memory-Integrated Retrieval-Augmented Captioning), a novel framework designed to address these issues through three core innovations: a cross-modal memory bank, adaptive dataset pruning, and a streaming decoder.
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