Targeting myeloperoxidase to reduce neuroinflammation in X-linked dystonia parkinsonism
Bibliographic record
Abstract
Although the genetic locus of X-linked dystonia parkinsonism (XDP), a neurodegenerative disease endemic in the Philippines, is well-characterized, the exact molecular mechanisms leading to neuronal loss are not yet fully understood. Recently, we demonstrated a significant increase in astrogliosis and microgliosis together with an increase in myeloperoxidase (MPO) levels in XDP post-mortem prefrontal cortex (PFC), suggesting a role for neuroinflammation in XDP pathogenesis. Here, we demonstrated a significant increase in MPO activity in XDP PFC using a novel specific MPO-activatable fluorescent agent (MAFA). Additionally, we demonstrated a significant increase in reactive oxygen species (ROS) in XDP-derived fibroblasts as well as in SH-SY5Y cells treated with post-mortem XDP PFC, further supporting a role for MPO in XDP. To determine whether increases in MPO activity were linked to increases in ROS, MPO content was immuno-depleted from XDP PFC [MPO(-)], which resulted in a significant decrease in ROS in SH-SY5Y cells. Consistently, the treatment with verdiperstat, a potent and selective MPO inhibitor, significantly decreased ROS in both XDP-derived fibroblasts and XDP PFC-treated SH-SY5Y cells. Collectively, our results suggest that MPO inhibition mitigates oxidative stress and may provide a novel therapeutic strategy for XDP treatment. Highlights: MPO activity is increased in XDP post-mortem prefrontal cortex.MPO activity is increased in cellular models of XDP.MPO increases reactive oxygen species (ROS) in vitro.Inhibiting MPO mitigates ROS in XDP.The MPO inhibitor, verdiperstat, dampens ROS suggesting a potential therapeutic strategy for XDP.
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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) | 0.001 | 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".