Abstract WP416: Specific Transcriptome Response in Neutrophils, Monocytes and Whole Blood in Human Intracerebral Hemorrhage and Ischemic Stroke of Different Etiologies
Bibliographic record
Abstract
Understanding transcriptome changes following intracerebral hemorrhage (ICH) and ischemic stroke (IS) of different etiologies, can lead to a better understanding of the molecular and cellular pathways involved in the response to acute brain injury caused by ICH and IS. We characterized the transcriptomic profiles from ICH and different IS etiologies to identify acute molecular changes in isolated monocytes, neutrophils and in whole blood. Peripheral blood was drawn from ICH (6) and IS (33) cases (cardioembolic, large vessel and lacunar) in the first 30 ± 20 hours post-onset of symptoms. We performed whole-genome RNA sequencing of whole blood (WB), and isolated neutrophils and monocytes. Control cases (10) with vascular risk factors (diabetes and/or hypertension and/or hypercholesterolemia) were also included (VRFC). A linear regression model including the interaction diagnosis x sample subtype with p<0.05 and overlap with FDR<0.2, (fold-change>1.2) was used for identifying differentially expressed (DE) genes. Gene ontology and pathway enrichment were performed for investigating the biological context of the DE. We observed specific transcriptional responses for ICH and IS, and within IS etiologies in monocytes, neutrophils and WB. Neutrophils’ response was the strongest with highest number of DE genes in both ICH and IS and its etiologies when compared to VRFC. Most of the changes were cell-type specific and involved immune response and signal transduction pathways. For example, in ICH compared to VRFC, about half of the over-represented pathways were unique to either monocytes or neutrophils. Many pathways over-represented in WB were not over-represented in monocytes or neutrophils, signifying the importance of additional blood cell types in the immune response to ICH and IS. A T-cell receptor gene was DE in WB only, and in opposite directions in ICH and IS when compared to VRFC, thus is a good biomarker candidate. The unique expression changes in neutrophils and monocytes after ICH and IS and its subtypes underscore their involvement in IS and ICH pathophysiology. The large number of unique genes and pathways in whole blood not detected in monocytes or neutrophils signify the contribution of other peripheral blood cell types to the ICH and IS responses.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".