Naphthaleneoxypropargyl-Containing Piperazine as a Regulator of Effector Immune Cell Populations upon an Aseptic Inflammation
Bibliographic record
Abstract
This study investigated the effects of aseptic inflammation and heavy metal exposure on immune responses, as well as the potential immunomodulatory properties of the newly synthesized 1-[1-(2,5-dimethoxyphenyl)-4-(naphthalene-1-yloxy)but-2-ynyl]-4-methylpiperazine complexed with β-cyclodextrin (β-CD). Aseptic inflammation was induced by a subcutaneous injection of turpentine in rats, while heavy metal exposure was achieved through a daily administration of cadmium chloride and lead acetate. The levels of immune cell populations, including cytotoxic T lymphocytes (CTL), monocytes, and granulocytes, were assessed in the spleen. The results showed that aseptic inflammation led to decreased levels of CTL, monocytes, and granulocytes on the 14th day, indicating an inflammatory response accompanied by a migration of effector cells to the inflamed tissues. The exposure to cadmium chloride and lead acetate resulted in systemic immunotoxic effects, with reduced levels of B cells, CD4+ Th cells, monocytes, and granulocytes in the spleen. Notably, piperazine complexed with β-CD (the complex) exhibited significant stimulatory effects on CD4+, CD8+, and myeloid cell populations during aseptic inflammation, even in the presence of heavy metal exposure. These findings suggest the potential immunomodulatory properties of the complex in the context of aseptic inflammation and heavy metal exposure.
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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".