Safety of Endoscopic-Ultrasound-Guided Portal Injection Chemotherapy using Drug-Eluting Microbeads in a Porcine Model
Bibliographic record
Abstract
Background and Aims: Patients with diffuse liver metastases have systemic chemotherapy as their only treatment option. We developed Endoscopic Ultrasound (EUS)-guided portal injection chemotherapy (EPIC) to increase drug levels in hepatic tissue as a novel new liver directed therapy. Methods: Sixteen anesthetized pigs were treated with 50 mg of irinotecan (n=8) or doxorubicin (n=8). Half (n=4) of the animals in each drug group were treated with EPIC-injected microbeads or EUS-guided chemotherapy without beads into the inferior vena cava (control). Animals were observed twice daily for 7 days for signs of clinical toxicities. Tissue samples were harvested for histology and drug levels. Blood counts and chemistries were determined pre-treatment and at 7 days. Results: No toxicities as evidenced by abnormal animal behavior were observed. No significant changes occurred in blood chemistry or blood counts in the irinotecan groups. For doxorubicin, systemic injection significantly decreased albumin, hemoglobin, and white blood cell count (P<.05), with no changes after EPIC. Hepatic histology showed mild foreign body reactions around the beads. No significant histologic changes were seen in other tissue sites. Neither irinotecan nor SN-38 was detectable at 7 days. For doxorubicin, no drug was detected in the plasma or bone marrow. The mean (SD) doxorubicin hepatic levels were non-significantly increased with EPIC vs control (181 [241] vs 151 [67] ng/g). Cardiac doxorubicin levels were significantly lower with EPIC (15 [4] vs 138 [48] ng/g; P=.02). Conclusions: EPIC using drug-eluting microbeads was safe in this animal model. For doxorubicin, EPIC may be safer than systemic injection.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".