Systematic analysis of the adverse effects of commonly used clinical tetracycline drugs based on the FAERS database.

BACKGROUND: Tetracyclines are a class of antibacterial drugs commonly used in clinical practice, but there is no systematic analysis of the adverse effects (AEs) of these drugs. We performed such pharmacovigilance analyses using the US Food and Drug Administration Adverse Event Reporting System (FAERS) database to explore tetracycline-related AEs. RESEARCH DESIGN AND METHODS: We used the pharmacovigilance analysis tool Open Vigil 2.1 to access FAERS data and obtained AE reports from January 2004 to June 2023, including doxycycline, minocycline, tigecycline, omadacycline, sarecycline, and eravacycline as the top suspect drugs. The signal value of the AE of the analyzed drug was calculated by the reporting odds ratio (ROR). RESULTS: A total of 15,020 cases were identified by analyzing drugs. In terms of adverse signals, doxycycline caused gastrointestinal mucosal necrosis (ROR = 1699.652); minocycline was reported to cause bone hyperpigmentation (ROR = 30976.223); tigecycline is responsible for blood fibrinogen decreased (ROR = 1714.078). CONCLUSIONS: AE reports of tetracycline drugs varied significantly. We found some AEs not mentioned in the instruction, such as the ototoxicity of tetracyclines. Doxycycline was associated with psychiatric side effects; minocycline presented in thyroid and skin tissue-associated tumors; abnormal signals were detected with eravacycline in the blood system.

Single-sensor rotating blade monitoring method under non-stationary conditions based on velocity and displacement.

A novel single-sensor method for monitoring rotating blade vibration is proposed and utilized to identify vibration parameters under the non-stationary condition. By analyzing the pulse-signal waveform, the blade tip displacement and vibration velocity are extracted. Then, the motion equation under the non-stationary condition is further developed to provide a theoretical basis. Finally, the optimization technology is applied to extract vibration parameters. Compared with multiple-sensor methods, the proposed method has lower installation difficulty, less equipment cost, fewer sensors, and no strict sensor layout requirement. Numerical simulations and experiments are conducted to validate the effectiveness and robustness of the proposed method. The relative error in the natural frequency does not exceed 0.1 %. Additionally, errors in other parameters are less than 8 % in the experiment.