2 Differential Transcriptomic Responses Among Burn Injury Outcomes Related to Morality and Hospital Length of Stay
Bibliographic record
Abstract
Abstract Introduction Severe burn injury induces a profound systemic molecular response. Yet, the various molecular mechanisms mediating clinical outcomes after burn injury are not well characterized. Using longitudinal global gene expression data, we investigate the evolution of transcriptomic responses to thermal injury. We hypothesized that burn patients with differing clinical outcomes will show diverging transcriptomic alterations over time. Methods This prospective observational study included patients from a regional burn center from 2013 to 2017. Patient demographics, burn injury characteristics, and blood samples for mRNA extraction and microarray whole genome gene expression profiling were collected at admission and set timepoints until 30 days. Patients were divided into 4 groups based on mortality status and hospital length of stay (LOS); G1 - died within 7 days, G2 - died after 7 days, G3 - discharged after 7 days, and G4 - discharged within 7 days. Transcriptomic abundances were compared between groups to identify differences in gene profiling. Pathway enrichment analysis was performed to determine the top significant pathways in each group. Results A total of 116 patients were analyzed. Most patients were male (72.4%) with a median age of 39 and TBSA of 12.3%. Overall mortality rate was 12.9%. The distribution of patients in G1 to G4 was 8%, 5%, 60%, and 27% respectively. A total of 1,245 blood samples and 17,289 transcripts were quantified. At admission, genes were differentially expressed in G1, G2 and G3 compared to G4 (FDR-corrected P < 0.05 and magnitude of log fold-change > 1). Significant gene sets were largely nonoverlapping, with only a few immune response related genes being activated across all groups. Pathway enrichment analysis showed significant up-regulated protein folding pathways in G1, and significant up-regulated pathways related to oxidative stress and temperature homeostasis in G3. Intra-individual transcriptomic changes from admission to 30 days showed distinct group- and time-dependent patterns. G4 showed the least pronounced transcriptomic response without any noticeable change over time, while G3 mounted a transcriptomic response that increased over time. Conclusions We identified transcriptomic alterations associated with distinct outcomes related to mortality and hospital LOS after burn injury. Alterations among groups were present at admission and persisted for 30 days. Connecting transcriptomic alterations to molecular mechanisms continues to evolve. Applicability of Research to Practice Enhanced understanding of transcriptomic alterations and molecular mechanisms of burn injury trajectories will allow for the development of early biomarkers, prognostic tools and novel intervention strategies.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".