Biosynthetic plasticity enables CD8+ T cell functional resilience under nutrient stress
Bibliographic record
Abstract
Summary / Abstract To maintain lineage-specific functions, cells must acquire and allocate nutrients across diverse cellular processes, even in metabolically-dysregulated environments. The mechanisms allowing CD8+ T cells to maintain immune function in perturbed environments are poorly understood. We find that CD8+ T cells adapt to nutrient stresses over time, reconfiguring gene-regulatory and metabolic networks to license functional recovery. Under acute stress, T cells reorient translational programming, limiting nutrient demand while prioritizing stress-sensitive metabolic and transcriptional responses. Within these responses, the transcription factors ATF4 and CEBPG jointly establish an adaptive metabolic program, promoting amino acid synthesis and uptake while maintaining mitochondrial anaplerosis. Despite diminished energetic capacity under environmental stress, this program prevents failure of central carbon metabolism, mitigating stress amplification and cellular dysfunction to potentiate anti-tumor immunity. Altogether, we demonstrate that biosynthetic plasticity via translational and metabolic reprioritization confers functional resilience to immune cells in unfavorable environments, offering novel strategies to enhance immunotherapies.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".