Expression of Simian Immunodeficiency Virus<i>nef</i>in Immune Cells of Transgenic Mice Leads to a Severe AIDS-Like Disease
Bibliographic record
Abstract
In order to study the functions of simian immunodeficiency virus (SIV) Nef in vivo in a small-animal model, we constructed transgenic (Tg) mice expressing the SIV(mac)239 nef gene in the natural target cells of the virus under the control of the human CD4 gene promoter (CD4C). These CD4C/SHIV-nef(SIV) Tg mice develop a severe AIDS-like disease, with manifestations including premature death, failure to thrive or weight loss, wasting, thymic atrophy, an especially low number of peripheral CD8+ T cells as well as a low number of peripheral CD4+ T cells, diarrhea, splenomegaly, and kidney (interstitial nephritis, segmental glomerulosclerosis), lung (lymphocytic interstitial pneumonitis), and heart disease. In addition, these Tg mice fail to mount a class-switched antibody response after immunization with ovalbumin, they produce anti-DNA autoantibodies, and some of them develop Pneumocystis carinii lung infections. All these results suggest a generalized Nef-induced immunodeficiency. The low numbers of peripheral CD8+ and CD4+ T cells are likely to reflect a thymic defect and may be similar to the DiGeorge-like "thymic defect" immunophenotype described for a subgroup of human immunodeficiency virus type 1-infected children. Therefore, it appears that SIV Nef alone expressed in mice, in appropriate cell types and at sufficient levels, can elicit many of the phenotypes of simian and human AIDS. These Tg mice should be instrumental in studying the pathogenesis of SIV Nef-induced phenotypes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".