Roflumilast, a cAMP-Specific Phosphodiesterase-4 Inhibitor, Reduces Oxidative Stress and Improves Synapse Functions in Human Cortical Neurons Exposed to the Excitotoxin Quinolinic Acid
Bibliographic record
Abstract
The overexpression of phosphodiesterase 4 (PDE4) enzymes is reported in several neurodegenerative diseases. PDE4 depletes cyclic 3′-5′ adenosine monophosphate (cAMP) and, in turn, cAMP response element-binding protein (CREB) and brain-derived neurotrophic factor (BDNF), the key players in cognitive function. The present study was undertaken to investigate the mechanism behind the protective effects of roflumilast (ROF), a cAMP-specific PDE4 inhibitor, against quinolinic acid (QUIN)-induced neurotoxicity using human primary cortical neurons. Cytotoxicity was analyzed using an MTS assay. Reactive oxygen species (ROS) and mitochondrial membrane potential were measured by DCF-DA and JC-10 staining, respectively. Caspase 3/7 activity was measured using an ApoTox-Glo Triplex assay kit. cAMP was measured using an ELISA kit. The protein expression of CREB, BDNF, SAP-97, synaptophysin, synapsin-I, and PSD-95 was analyzed by the Western blotting technique. QUIN exposure down-regulated CREB, BDNF, and synaptic protein expression in neurons. Pretreatment with ROF increased the intracellular cAMP, mitochondrial membrane potential, and nicotinamide adenine dinucleotide (NAD + ) content and decreased the ROS and caspase 3/7 levels in QUIN-exposed neurons. ROF up-regulated the expression of synapse proteins SAP-97, synaptophysin, synapsin-I, PSD-95, and CREB and BDNF, which indicates its potential role in memory. This study suggests for the first time that QUIN causes pre- and postsynaptic protein damage. We further demonstrate the restorative effects of ROF on the mitochondrial membrane potential and antiapoptotic properties in human neurons. These data encourage further investigations to reposition ROF in neurodegenerative diseases and their associated cognitive deficits.
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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) | 0.001 | 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 | 0.001 |
| 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".