DNA damage and brain trauma: a clue to pathophysiology and biomarker development
Bibliographic record
Abstract
Mild traumatic brain injury (mTBI) or concussion is a very common occurrence in contact sports, and can cause brain damage with long-term symptoms, including depression, aggression, memory loss, and an increased risk of neurodegeneration later in life. Recently, there has been increased attention towards concussion in sport both in research and media, however the nature and pathophysiology of mTBI-induced neurodegeneration remain unknown. The objective of this study is to identify early pathophysiological markers of TBI. This study used a collection of donated postmortem brains with a history of repetitive mTBI in contact sports and non-TBI control brains. Nanostring ncounter’s immune panel was used to evaluate gene expression, and results showed that brains with a history of TBI tended to group with significantly older brains with no history of TBI in regards to their immune profile. Further analysis of this expression panel revealed that genes associated with senescence and secretory phenotype were upregulated in brains with a history of mTBI. Additionally, immunohistochemistry for γ-H2AX (a marker for double stranded DNA breaks) showed that brains with a history of repetitive TBI accumulated a spectrum of DNA damages not present in controls. This damage was widespread and involved mainly glial cells including oligodendrocytes, and astrocytes. The latter showed morphological changes reminiscent of senescence, including soma swelling and beading of processes. Further, these changes were accompanied by translocation of structural nuclear proteins. These changes preceded the appearance of abnormal protein deposition in the brain. Overall, these results suggest that DNA damage and cellular senescence are upstream events in the manifestation of post-mTBI symptoms and pathology, and represent promising opportunities for discovery of biomarkers for early TBI detection and follow-up of progression. LEARNING OBJECTIVES The presentation will enable the learner to: 1. Explore the relationship between trauma and DNA structural changes 2. Explore the relationship between trauma and senescence
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".