[Intralymphatic chemotherapy with adriamycin-adsorbing nanometric activated carbon:pharmacokinetic experiment with dogs].
Bibliographic record
Abstract
OBJECTIVE: To observe the pharmacokinetics of adriamycin-adsorbing nanometric activated carbon in intralymphatic chemotherapy. METHODS: Two ml of suspension of activated carbon with the diameter of 21 nm was mixed with adriamycin 5 mg. Eighteen dogs were randomly divided into 6 equal groups. The above mentioned mixture was injected subserosally to the anterior wall of gastric antrum of the dogs. Thirty minutes, 1 h, 2 h, 1 day, and 3 days after the injection the gastroepiploic lymph nodes of the Groups 1 - 5 were obtained. And Group 6 underwent extraction of venous blood samples 5, 15, 30, 60, 120, and 240 minutes after the injection and extraction of thoracic duct fluid 5, 15, 30, 60, 120, 240, and 360 minutes after the injection. The adriamycin concentrations at different time points were determined by mass spectrometer. The lymphatic vessels and nodes at the gastric wall were observed by the naked eyes. RESULTS: Black tiny lymphatic vessels and lymph nodes were visualized around the injection areas immediately after the injection. Adriamycin content could be detected 30 min after the injection and lasted for 72 h at high levels with the peak content of (84.6 +/- 2.0) microg per gram tissue at 60 min in the perilymph node of gastroepiploic artery. The adriamycin concentration in the lymph fluid of thoracic duct reached the top level of 162.5 ng/ml 30 min after the injection, and then decreased slowly. Adriamycin could be still detected in lymph fluid 6 h after injection. No trace of adriamycin was found in the blood at any time points. CONCLUSION: The content of adriamycin can keep high and last long in the drainage of lymph node and lymph fluid in the treatment of intralymphatic chemotherapy using adriamycin-adsorbing nanometric activated carbon.
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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 | 0.000 |
| 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".