Pharmacokinetics of Cationic Liposome-Encapsulated Doxycycline in Mice Challenged with Genital Infection by <i>Chlamydia trachomatis</i>
Bibliographic record
Abstract
Our previous studies demonstrated the efficacy of cationic liposome-encapsulated doxycycline (CaL-DOX) on the course of infection with Chlamydia trachomatis in vitro and in vivo. In this investigation, the pharmacokinetics of CaL-DOX are reported. Female mice inoculated intravaginally with 4.84 x 10(5) inclusion-forming units were treated intramuscularly, 3 days postinfection, as determined by a preliminary study, with 0.1 ml of unencapsulated doxycycline (DOX) or CaL-DOX, at 10 microg/ml body weight for 3 consecutive days. Sampling was performed at 12, 24, 48, 72 and 96 h after treatment. The microbiological test was used to measure the DOX concentration in sera, liver, kidneys and genital organs. The maximum concentration in kidneys, liver and genital organs was higher in mice treated with DOX than in those treated with CaL-DOX. However, in sera, the amount was similar to that in mice treated with DOX. The DOX concentration found in mice treated with CaL-DOX was much less than in those treated with unencapsulated DOX. This may have a direct impact on the secondary effects caused by the medication. Decreased secondary effects should have a positive outcome on patient physical and mental health. Even if this study is the only one of its kind so far, CaL-DOX could be an alternative solution for the treatment of chlamydial infections.
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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".