Examining Efficacy of Kidney-Targeted Nanoparticle Immunosuppressant Therapy on Lupus Nephritis in a Murine Autoimmune Disease Model
Bibliographic record
Abstract
Introduction: Lupus nephritis (LN) is a severe kidney manifestation of systematic lupus erythematosus (SLE) with no known cure. Although typically treated with immunosuppressants, these medications can cause toxic side effects. This study proposes adopting mesoporous silica nanoparticles binding to a kidney-specific ligand, megalin, to locally deliver the immunosuppressive agent with no nephrotoxicity, mycophenolate mofetil. It is hypothesized that this method would inhibit LN progression by locally modulating immune cell activity. Methods: Silica nanoparticles are linked to the amino groups (-NH2) and polyethyleneimine and conjugated to megalin. These conjugated nanoparticles (NPs) are then loaded with the immunosuppressant mycophenolate mofetil (MMF). The affinity and specificity of these NPs are confirmed using in vitro and ex vivo methods. Murine autoimmune disease mice (MRL-lpr) are used as a model for SLE. The mice received different nanoparticle treatments either conjugated with megalin or not, carrying MMF or not, and not receiving free MMF treatment to investigate the efficacy of megalin-conjugated mesoporous silica nanoparticles (MSN-NPs) at preventing LN. Indicators of health measured included proteinuria and anti-dsDNA concentration, kidney and lymphadenopathy scores and absolute cell counts of leukocytes, T-cells and B-cells from the kidney and other organs as well. Results: Megalin-conjugated MSN-NPs are anticipated to increase MMF bioavailability within the kidney compared to non-specific MSN-NPs. The mice receiving megalin-conjugated MSN-NPs carrying MMF are expected to decrease proteinuria at the nephrotic range and attenuate local inflammatory immune cell activity. Moreover, it is anticipated that there will be a decrease in lymphatic cell numbers, lymph node size, and repressed inflammation in kidney glomerular and tubulointerstitial regions. Discussion: Targeted NP immunosuppressant drug delivery is expected to be the most effective at alleviating LN in SLE mice, compared to non-megalin conjugated NP or free drug. Future directions could be investigating toxicity and off-target effects of this drug, other kidney cell markers as targets, and non-human primates as test candidates. Conclusion: Although megalin-conjugated MSN-NPs carrying MMF has potential for alleviating LN in SLE, a rigorous test of both capacity, safety, and off-targets effects are required to fully appreciate its clinical efficacy.
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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 | 0.001 |
| 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".