"The effect of 48-weeks azithromycin therapy on levels of soluble biomarkers associated with HIV-associated chronic lung disease"

"Pleiotropic" Effects of Antibiotics: New Modulators in Human Diseases

Antibiotics, widely used medications that have significantly increased life expectancy, possess a broad range of effects beyond their primary antibacterial activity. While some are recognized as adverse events, others have demonstrated unexpected benefits. These adjunctive effects, which have been defined as "pleiotropic" in the case of other pharmacological classes, include immunomodulatory properties and the modulation of the microbiota. Specifically, macrolides, tetracyclines, and fluoroquinolones have been shown to modulate the immune system in both acute and chronic conditions, including autoimmune disorders (e.g., rheumatoid arthritis, spondyloarthritis) and chronic inflammatory pulmonary diseases (e.g., asthma, chronic obstructive pulmonary disease). Azithromycin, in particular, is recommended for the long-term treatment of chronic inflammatory pulmonary diseases due to its well-established immunomodulatory effects. Furthermore, antibiotics influence the human microbiota. Rifaximin, for example, exerts a eubiotic effect that enhances the balance between the gut microbiota and the host immune cells and epithelial cells. These pleiotropic effects offer new therapeutic opportunities by interacting with human cells, signaling molecules, and bacteria involved in non-infectious diseases like spondyloarthritis and inflammatory bowel diseases. The aim of this review is to explore the pleiotropic potential of antibiotics, from molecular and cellular evidence to their clinical application, in order to optimize their use. Understanding these effects is essential to ensure careful use, particularly in consideration of the threat of antimicrobial resistance.

Exhaled nitric oxide is associated with inflammatory biomarkers and risk of acute respiratory exacerbations in children with HIV-associated chronic lung disease

OBJECTIVES

Chronic lung disease is a recognized complication in children with HIV. Acute respiratory exacerbations (ARE) are common among this group and cause significant morbidity. Exhaled nitric oxide (eNO) is a known marker of local airway inflammation. We investigated the association between eNO and ARE, biomarkers of systemic inflammation, and the effect of azithromycin on eNO levels.

METHODS

Individuals aged 6-19 years with HIV-associated chronic lung disease in Harare, Zimbabwe, were enrolled in a placebo-controlled randomized trial investigating the effect of 48-week azithromycin treatment on lung function and ARE. eNO levels and biomarkers were measured at inclusion and after treatment in a consecutively enrolled subset of participants. Linear regression and generalized linear models were used to study associations between eNO and ARE, biomarkers, and the effect of azithromycin on eNO levels.

RESULTS

In total, 172 participants were included in this sub-study, 86 from the placebo group and 86 from the azithromycin group. Participants experiencing at least one ARE during follow-up had significantly higher eNO levels at baseline than participants who did not (geometric mean ratio 1.13, 95% confidence interval [CI] 1.03-1.24, p = 0.015), adjusted for trial arm, age, sex and history of tuberculosis. Matrix metalloproteinase (MMP)-3, -7, and -10 were significantly associated with higher baseline eNO levels. At 48 weeks, azithromycin treatment did not affect eNO levels (geometric mean ratio 0.86, 95% CI 0.72-1.03, p = 0.103).

CONCLUSION

Higher baseline eNO levels were a risk factor for ARE. eNO was associated with proinflammatory biomarkers previously found to contribute to the development of chronic lung disease. The potential use of eNO as a marker of inflammation and risk factor for ARE in HIV-associated chronic lung disease needs further investigation.

Artificial-Intelligence-Based Models Coupled with Correspondence Analysis Visualization on ART—Cases from Gombe State, Nigeria: A Comparative Study

Antiretroviral therapy (ART) is the common hope for HIV/AIDS-treated patients. Total commitments from individuals and the entire community are the major challenges faced during treatment. This study investigated the progress of ART in the Federal Teaching Hospital in Gombe state, Nigeria by using various records of patients receiving treatment in the ART hospital unit. We combined artificial intelligence (AI)-based models and correspondence analysis (CA) techniques to predict and visualize the progress of ART from the beginning to the end. The AI models employed are artificial neural networks (ANNs), adaptive neuro-fuzzy inference systems (ANFISs) and support-vector machines (SVMs) and a classical linear regression model of multiple linear regression (MLR). According to the outcome of this study, ANFIS in both training and testing outperformed the remaining models given the R2 (0.903 and 0.904) and MSE (7.961 and 3.751) values, revealing that any increase in the number of years of taking ART medication will provide HIV/AIDS-treated patients with safer and elongated lives. The contingency results for the CA and the chi-square test did an excellent job of capturing and visualizing the patients on medication, which gave similar results in return, revealing there is a significant association between ART drugs and the age group, while the association between ART drugs and marital status (93.7%) explained a higher percentage of variation compared with the remaining variables.