Abstract WP564: Deep Immune Profiling of the Post-Stroke Peripheral Immune Response Reveals Tri-phasic Response and Correlations With Long-Term Cognitive Outcomes
Bibliographic record
Abstract
Introduction: Stroke produces profound local and systemic immune responses that engage all major innate and adaptive immune compartments. The aim of this study was to characterize the systemic immune response to stroke and to determine if it contributes to long-term cognitive disability. Methods: We included 24 consecutive subjects with ischemic stroke and excluded patients for autoimmune disorders, use of immunosuppressant drugs, or life expectancy <90 days. Blood samples were collected for up to 9 timepoints after stroke (days 1, 2, 3, 5, 7, 14, 30, 90, and 365). Change in cognitive function between days 90 and 365 was assessed using the Montreal Cognitive Assessment (MoCA). Control samples were from a cohort of 24 sex- and age-matched patients prior to hip replacement surgery. We used mass cytometry to acquire 240 immune features from each sample, representing 20 immune cell subtypes, their frequency, cell surface markers, and activation states. Elastic Net (EN) regularized regression modeling was used to characterize phases of the immune response and to correlate stages of the immune response with change in cognitive function. Results: The EN model identified three distinct phases of the systemic immune response to ischemic stroke: The acute phase (day 2) was characterized by increased STAT3 (signal transducer and activator of transcription 3) signaling responses in innate immune cell types. The intermediate phase (day 5) was characterized by increased CREB (cAMP response element-binding protein) signaling responses in adaptive immune cell types. The late phase (day 90) was characterized by persistent elevation of neutrophils and IgM+ B cells. By day 365 there was a return to baseline immune responses, comparable to the controls. A decline in MoCA scores between day 90 and day 365 after stroke correlated with a stronger inflammatory response in the acute phase (r = -0.692, Bonferroni-corrected p = 0.04). Conclusions: The results demonstrate three distinct phases of the peripheral immune response that occur after stroke, spanning from days 2 to day 90. The acute phase immune response predicts post-stroke cognitive decline, suggesting that therapies aimed at optimizing this response could lead to preservation of cognitive functioning post-stroke.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".