The retrograde transport of BDNF and proNGF diminishes with age in basal forebrain cholinergic neurons
Bibliographic record
Abstract
Sesame (Sesamum indicum Linn.) is one of the tropical oil crops mainly found in Thailand, China, India, and Africa.It is an important culinary and traditional Chinese medicine.Several lines of research have confirmed its medicinal properties in antimicrobial, anticancer, anti-inflammation, and antioxidant.It contains nutraceutical sources of lignans especially sesamol.The exact mechanism of sesamol involved in neuroprotection still remains to be elucidated.Herein, the neuroprotective effects of sesamol against H 2 O 2 -induced oxidative stress were investigated.The results indicated that pretreatment with 1 M sesamol significantly increased H 2 O 2 -induced cell viability, as determined by MTT and Annexin V apoptosis detection.Protein expression of apoptotic markers (BCL-2 and BAX) was significantly altered in the event of oxidative stress.Sesamol-pretreated cells elicited significant downregulation of BAX apoptotic protein and upregulation of anti-apoptotic BCL-2.Moreover, intracellular reactive oxygen species (ROS) generation induced by H 2 O 2 was determined by DCFDA assay and further confirmed by fluorescence microscope.The ROS production was decreased by pretreatment with 1 M sesamol compared to the H 2 O 2 alone.Meanwhile, the levels of antioxidant markers (SOD and CAT) were significantly increased in sesamol-pretreated cells due to oxidative stress.To better understand the molecular mechanisms of sesamol involved in prevention of neurodegeneration, protein expression levels of SIRT1, SIRT3, and FOXO3a were evaluated.Surprisingly, sesamol clearly maintained SIRT1, SIRT3, and FOXO3a under oxidative stress.These data suggest that sesamol protects neuronal cells against oxidative stress through SIRT1-SIRT3-FOXO3a signaling pathway.Besides, Molecular docking data also revealed that sesamol could be docked well with SIRT1, which is similar to the reference compound.Hence, this bioactive compound might be one of the promising natural agents for the prevention and/or treatment of neurodegenerative diseases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".