Evaluation of the toxicity and efficacy of a multi-target polymer-drug nano-polyplex in SH-SY5Y cells and Drosophila model of tauopathy
Bibliographic record
Abstract
Hyperphosphorylated tau contributes to synaptic damage and neuronal dysfunction in neurodegenerative diseases such as Alzheimer's disease (AD), making it a key therapeutic target. This study evaluated the toxicity and therapeutic potential of a novel polymer-drug nano-polyplex, N5NM15, and polyacrylic acid (PAA) in Drosophila tauopathy models and undifferentiated human SH-SY5Y cells. Cellular uptake was demonstrated by N5NM15, and SH-SY5Y cell viability was significantly enhanced (45%, p ≤ 0.0001) under okadaic acid-induced stress, and total tau levels were reduced (1.43-fold, p ≤ 0.01). In comparison, PAA had a modest effect on decreasing tau phosphorylation (1.3-fold) at the pSer202/pThr205 site. Toxicity studies in Drosophila revealed that N5NM15 (3.5:1 and 44:12.5 µg/mL) and PAA (44 µg/mL) were toxic to adult flies expressing the eye-specific driver (GMR-GAL4) but were well-tolerated in flies overexpressing the pan-neuronal driver ELAV-GAL4. Furthermore, treatment with N5NM15 and PAA did not improve the ommatidial arrangement, eye bristle count, or eye length in tauopathy models. Climbing and survival assays indicated a potential mild protective effect at a lower concentration (3.5:1 µg/mL) at the early stage of the disease, but at a higher dose (44:12.5 µg/mL) was significantly toxic, in both wild-type (p ≤ 0.0001) and tauopathy models (p < 0.05). These findings highlight the need for N5NM15 and PAA dose optimisation and reformulation with non-toxic buffers to enhance therapeutic potential while minimising adverse effects in normal and Drosophila tauopathy models for AD treatment.
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 | 0.000 |
| 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) | 0.000 | 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".