HIV-1 ANTISENSE PROTEIN: ROLE IN VIRAL PATHOGENESIS

The HIV-1 antisense protein (ASP) is expressed from an open reading frame (ORF) on the negative strand of the viral genome, which overlaps the env gene on the positive strand. As a de novo protein, ASP has no known homologs. The existence of ASP was first proposed over three decades ago. Yet, whether ASP is expressed in vivo and whether it plays a role in the HIV-1 lifecycle remains controversial. The presence of a full-length ASP ORF exclusively in the pandemic group M HIV-1 and its conservation in ~77% of strains within this group suggests that ASP may offer an evolutionary advantage to the virus. Thus, the purpose of the studies described in this thesis was to determine whether ASP plays a role in HIV-1 replication. To that end, we generated ASP knockout/knockdown (KO/KD) HIV-1 strains by introducing single nucleotide mutations that either disable the start codon of the ASP ORF or insert premature stop codons. ASP-deficient strains were derived from three different HIV-1 clones: the CCR5 (R5)-tropic strains, JRCSF and 49.5, and the CXCR4 (X4)-tropic strain NL4-3. In vitro infection of primary CD4+ T cells with wildtype and ASP KO/KD viruses showed that the latter replicates at lower rates. Moreover, infection of immunodeficient mice reconstituted with PBMCs from healthy human donors demonstrated that one of the ASP KO/KD strains also has significantly reduced replication in vivo. To further explore the underlying mechanisms of ASP action, we examined the infectivity of HIV-1 viral particles immunoprecipitated by an anti-ASP antibody and reached the conclusion that ASP is present on infectious HIV-1 particles. Since previous studies have shown that ASP is present also on the surface of productively infected cells, we hypothesize that ASP may be involved in facilitating HIV-1 entry or that it may be able to signal through cellular surface receptors to benefit HIV-1 replication. In conclusion, this study shows for the first time that ASP promotes viral replication. It also demonstrates the presence of ASP on infectious HIV-1 virions, providing a direction for future ASP functional research

Trustworthy Large Models in Vision: A Survey

The rapid progress of Large Models (LMs) has recently revolutionized various fields of deep learning with remarkable grades, ranging from Natural Language Processing (NLP) to Computer Vision (CV). However, LMs are increasingly challenged and criticized by academia and industry due to their powerful performance but untrustworthy behavior, which urgently needs to be alleviated by reliable methods. Despite the abundance of literature on trustworthy LMs in NLP, a systematic survey specifically delving into the trustworthiness of LMs in CV remains absent. In order to mitigate this gap, we summarize four relevant concerns that obstruct the trustworthy usage in vision of LMs in this survey, including 1) human misuse, 2) vulnerability, 3) inherent issue and 4) interpretability. By highlighting corresponding challenge, countermeasures, and discussion in each topic, we hope this survey will facilitate readers' understanding of this field, promote alignment of LMs with human expectations and enable trustworthy LMs to serve as welfare rather than disaster for human society