Fluoroquinolones-related psychiatric adverse events: a real‑world retrospective and pharmacovigilance database analysis

OBJECTIVE

The purpose of this study was to evaluate the pharmacovigilance and clinical characteristics of psychiatric adverse events(AEs) related to Fluoroquinolones(FQs), and to determine the risk factors for timely management.

METHODS

Data about AE reporting comes from the FDA Adverse Event Reporting System (FAERS) database, which was used for pharmacovigilance assessments. In addition, we also analyzed the cases of psychiatric AEs related to FQs retrospectively.

RESULTS

Both of the FAERS database analysis and literature reports show that the proportion of FQs-related psychiatric AEs reported in females were higher (51.11% VS 33.44% and 53.23% VS 46.77%). Both of them show that the proportion of psychiatric AEs caused by FQs was higher in the age groups of 19-44 (28.08% and 40.32%) and 45-64 (28.17% and 25.81%). Most psychiatric AEs occurred within 10 days after FQs administration. Literature shows that 67.74% of the psychiatric AEs disappeared within 3 days after drug withdrawal (some cases were accompanied by other drug).

CONCLUSION

Psychiatric AEs caused by FQs are serious, and there are many important safety signals that have not been mentioned in the label or previous studies. It is very important to identify and manage psychiatric AEs in time for the safe use of FQs.

Differences in nature killer cell response and interference with mitochondrial DNA induced apoptosis in moxifloxacin environment

OBJECTIVES

As antibiotics become more prevalent, accuracy and safety are critical. Moxifloxacin (MXF) have been reported to have immunomodulatory effects on a variety of immune cells and even anti-proliferative and pro-apoptotic effects, but the mechanism of action is not fully clear.

METHODS

Peripheral blood mononuclear cells (PBMC) from experimental groups of healthy adults (n = 3) were treated with MXF (10ug/ml) in vitro for 24 h. Single-cell sequencing was performed to investigate differences in the response of each immune cell to MXF. Flow cytometry determined differential gene expression in subsets of most damaged NK cells. Pseudo-time analysis identified drivers that influence MXF-stimulated cell differentiation. Detection of mitochondrial DNA and its involvement in the mitochondrial respiratory chain pathway clarifies the origin of MXF-induced stress injury.

RESULTS

Moxifloxacin-environmental NK cells are markedly reduced: a new subset of NK cells emerges, and immediate-early-response genes in this subset indicate the presence of an early activation response. The inhibitory receptor-dominant subset shows enhanced activation, leading to increased expression of cytokines and chemokines. The near-mature subset showed greater cytotoxicity and the most pronounced cellular damage. CD56bright cells responded by antagonizing the regulation of activation and inhibitory signals, demonstrating a strong cleavage capacity. The severe depletion of mitochondrial genes was focused on apoptosis induced by the mitochondrial respiratory chain complex.

CONCLUSION

NK cells exhibit heightened sensitivity to the MXF environment. Different NK subsets upregulate the expression of cytokines and chemokines through different activation pathways. Concurrently, MXF induces impairment of the mitochondrial oxidative phosphorylation system, culminating in apoptosis.

Depressive and Other Adverse CNS Effects of Fluoroquinolones

Fluoroquinolones (FQs) are widely used drugs around the world. This is a result of their broad spectrum of antibacterial activity, high bioavailability, and known efficacy. Since they appeared on the market, their prescribing frequency has gradually increased. In 2011, FQs became the third most prescribed class of antibiotics in the US. Widespread use of these drugs resulted in an increasing number of reported side effects. In 2016, the FDA warned about significant side effects, including mental disorders in the form of anxiety, psychotic symptoms, insomnia, and depression. Psychiatric adverse reactions to FQs occur with a frequency of 1 to 4.4% and the mechanism of their formation is not entirely clear. It is believed that the antagonistic effect of FQs on the GABA receptor or interaction with the main receptor for the glutamatergic system-NMDA-is responsible for this. The paper is a structured review of 68 selected publications and the latest summary of CNS adverse effects that occur during FQ use. Prescribers should be aware of the risk factors for FQ toxicity, including elderly patients with underlying medical conditions or receiving concomitant medication; however, these adverse events may also occur in other groups of patients.

GPCR_LigandClassify.py; a rigorous machine learning classifier for GPCR targeting compounds

The current study describes the construction of various ligand-based machine learning models to be used for drug-repurposing against the family of G-Protein Coupled Receptors (GPCRs). In building these models, we collected > 500,000 data points, encompassing experimentally measured molecular association data of > 160,000 unique ligands against > 250 GPCRs. These data points were retrieved from the GPCR-Ligand Association (GLASS) database. We have used diverse molecular featurization methods to describe the input molecules. Multiple supervised ML algorithms were developed, tested and compared for their accuracy, F scores, as well as for their Matthews' correlation coefficient scores (MCC). Our data suggest that combined with molecular fingerprinting, ensemble decision trees and gradient boosted trees ML algorithms are on the accuracy border of the rather sophisticated deep neural nets (DNNs)-based algorithms. On a test dataset, these models displayed an excellent performance, reaching a ~ 90% classification accuracy. Additionally, we showcase a few examples where our models were able to identify interesting connections between known drugs from the Drug-Bank database and members of the GPCR family of receptors. Our findings are in excellent agreement with previously reported experimental observations in the literature. We hope the models presented in this paper synergize with the currently ongoing interest of applying machine learning modeling in the field of drug repurposing and computational drug discovery in general.

Effect of ciprofloxacin vs levofloxacin on QTc-interval and dysglycemia in diabetic and non-diabetic patients

BACKGROUND

Levofloxacin and ciprofloxacin are more commonly used amongst fluoroquinolone class and the question of cardiac safety and glucose hemostasis of this class has been raised.

OBJECTIVE

To compare intravenous levofloxacin and ciprofloxacin regarding their risk on QTc prolongation and dysglycemia in diabetic and non-diabetic patients.

METHODS

A randomised prospective study at Beni-Suef university hospital was conducted on 200 adult patients over 6 months. The patients received intravenous levofloxacin 750mg once daily or ciprofloxacin 400mg twice daily. Electrocardiogram and fasting blood glucose were obtained from each patient before starting the antibiotic, 24 hours, 72 hours after the first dose, and 72 hours after antibiotics cessation.

RESULTS

The results of the current study showed the relative risk for QTc prolongation with levofloxacin was more than ciprofloxacin by about 4 and 1.5 times in diabetic and non-diabetic patients, respectively. The relative risk for dysglycemia with levofloxacin was 2.28 and 1.39 times more than ciprofloxacin in diabetic and non-diabetic patients, respectively.

CONCLUSION

The present study showed that the risk for QTc prolongation and hyperglycemia was greater with levofloxacin than ciprofloxacin in diabetic and non-diabetic patients. In addition, the risk for hypoglycemia was greater with levofloxacin than ciprofloxacin in non-diabetic patients.