Detection and Role of Feline Apolipoprotein B mRNA-editing Enzyme Catalytic Polypeptide Subunit 3G-Like Protein in Feline Cells and Tissues
Bibliographic record
Abstract
Abstract The innate host defence system is designed to resist pathogenic microorganism infections. Despite the compelling scientific evidence, our understanding of the full potential of the mechanism is still unclear due to the complex interactions between hosts and invaders. We previously reported latency in cat mucosal infected with low-dose cell-associated feline immunodeficiency virus (10 2 and 10 3 infected cells). Here we investigated the expression of Apolipoprotein B mRNA-editing enzyme catalytic subunit 3G (APOBEC3G or A3G) in feline cells and tissues and whether its presence antagonizes the viral pre-integration complex resulting in partial or complete FIV latency. Total RNA and protein lysates were collected from cell lines, blood, and tissue samples. Real-time RT-PCR and western blot assays were used to quantify fA3G-like protein in cats exposed to high versus low-dose cell-associated FIV. We consistently detected fA3G-like protein in mock T-cell lines (E-CD4+, MYA-1, Crandell feline kidney cells) and primary bone marrow-derived macrophages with variable expressions in feline peripheral blood mononuclear cells (PBMC). In addition, the fA3G-like protein was found to interact with FIV group-specific antigen (Gag) protein through immunoprecipitation assays. The protein expression was utterly abrogated following FIV infection. However, in lytic FIV infection (in vivo), fA3G-like protein decreased in early post-infection, whereas latently infected cats showed stable expression. These data are the first report of the fA3G-like protein expression in felines and its abrogation in lytic but not in latent FIV-infected individuals. These results might provide new insight into the role of fA3G-like protein in the host defence mechanism against retrovirus infections.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".