Prevention of thymus involution rescues old mice from fatal Toxoplasma gondii infection
Bibliographic record
Abstract
Abstract Thymic epithelial cells (TEC) make up the thymic microenvironments that support the generation of a functionally competent and self-tolerant T-cell repertoire. Infections, starvation, and aging, among other factors, cause thymus involution with loss of T-cell generation and decreased frequency of naive T-cells in secondary lymphoid organs. However, the causes and consequences of thymus involution are not clearly understood. Since thymus function declines with involution, we need a better understanding how the thymus controls T cell development. We found that constitutive overexpression of Myc (cMycTg) in TEC prevents thymus involution, causing a dramatic increase in thymus size in adult mice (Cowan et al, 2019). In addition, cMycTg mice restored frequencies of CD4+ and CD8+ naive T-cell populations to the levels observed in young adult mice. In unpublished work, we have found that prevention of thymus involution rescues aging mice from lethal Toxoplasma gondii infection. During the acute infection, old mice showed a significantly decreased frequency of parasite-specific T-cells and increased serum levels of IFNγ, IL6 and TNFα. Furthermore, antibody depletion of T-cells in aging mice challenged with Toxoplasma gondii prolonged their survival. These findings identify a role for thymic involution in the age-associated mortality of Toxoplasma gondii infection. We are now investigating the mechanisms responsible for the pathogenic immune responses seen in aged individuals to understand how improved thymic function modifies immune responses. AMS is supported by the patronage of the Children’s Hospital of Mexico. SCS, JEC and AB are supported by the NIH Intramural Cancer Research Training Award to post-doctoral fellows.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".