New Avenues for Nanoparticle-Related Therapies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Development of nanoparticle-based drug delivery systems has been attempted for the treatment of cancer over the past decade. The enhanced permeability and retention (EPR) effect is the major mechanism to passively deliver nanodrugs to tumor tissue. However, a recent systematic review demonstrated limited success of these studies, with the clearance of nanoparticles by the mononuclear phagocytic system (MPS) being a major hurdle. Herein, we propose that nanotechnologists should reconsider their research focuses, aiming for therapeutic targets other than cancer. Treatments for diseases that do not (or less) rely on EPR should be considered, such as active targeting or MPS evasion systems. For example, systemic delivery of drugs through intravenous injection can be used to treat sepsis, multi-organ failure, metabolic disorders, blood diseases, immune and autoimmune diseases, etc. Local delivery of nanodrugs to organs such as the lung, rectum, or bladder may enhance the local drug concentration with less clearance via MPS. In transplant settings, ex vivo organ perfusion provides a new route to repair injury of isolated organs in the absence of MPS. Based on a similar concept, chemotherapy with in vivo lung perfusion techniques and other isolated organ perfusion provides opportunities for cancer therapy.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 it