Lymphocyte Death in a Mouse Model of Ebola Virus Infection
Bibliographic record
Abstract
BACKGROUND: A striking feature of Zaire Ebola virus (ZEBOV) infection in nonhuman primates is the rapid depletion of T and NK lymphocytes by apoptosis. In a mouse model of ZEBOV infection, lymphocyte death is a prominent finding; however, the mechanism of death and the lymphocyte subsets that are targeted remain unknown. METHODS: We extended the characterization of lymphocyte death in a mouse model of ZEBOV infection by evaluating lymphocytes during the course of disease, using flow cytometry, electron microscopy, and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick-end labeling (TUNEL). RESULTS: B cell, CD4+ and CD8+ T cell, and NK cell counts all dropped dramatically in the blood of infected BALB/c mice, and lymphocyte death was observed in the spleen by means of TUNEL staining and in the blood by means of electron microscopy. Morphologically, lymphocyte death occurred by both classic apoptosis and apoptosis-like programmed cell death. CONCLUSIONS: The early and severe loss of peripheral blood NK and CD8+ lymphocytes in ZEBOV-infected mice is similar to that seen in macaques. The morphological basis of lymphocyte death in ZEBOV-infected mice appears to be both classic apoptosis and apoptosis-like programmed cell death, although lymphocyte apoptosis in ZEBOV-infected nonhuman primates seems to occur primarily via classic apoptosis. The mouse model of ZEBOV infection may be useful for the screening of therapeutics directed against limiting lymphocyte death.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".