A Novel Formulation of Tigecycline Has Enhanced Stability and Sustained Antibacterial and Antileukemic Activity
Bibliographic record
Abstract
Tigecycline is a broad-spectrum, first-in-class glycylcycline antibiotic currently used to treat complicated skin and intra-abdominal infections, as well as community-acquired pneumonia. In addition, we have demonstrated that tigecycline also has in vitro and in vivo activity against acute myeloid leukemia (AML) due to its ability to inhibit mitochondrial translation. Tigecycline is relatively unstable after reconstitution, and this instability may limit the use of the drug in ambulatory infusions for the treatment of infection and may prevent the development of optimal dosing schedules for the treatment of AML. This study sought to identify a formulation that improved the stability of the drug after reconstitution and maintained its antimicrobial and antileukemic activity. A panel of chemical additives was tested to identify excipients that enhanced the stability of tigecycline in solution at room temperature for up to one week. We identified a novel formulation containing the oxygen-reducing agents ascorbic acid (3 mg/mL) and pyruvate (60 mg/mL), in saline solution, pH 7.0, in which tigecycline (1 mg/mL) remained intact when protected from light for at least 7 days. This formulation also preserved the drug's antibacterial and antileukemic activity in vitro. Moreover, the novel formulation retained tigecycline's antileukemic activity in vivo. Thus, we identified and characterized a novel formulation for tigecycline that preserves its stability and efficacy after reconstitution.
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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".