Mechanism of action of Orthosiphon stamineus against non-alcoholic fatty liver disease: Insights from systems pharmacology and molecular docking approaches

Non-alcoholic fatty liver disease (NAFLD) is one of the most common complications of a metabolic syndrome caused by excessive accumulation of fat in the liver. Orthosiphon stamineus also known as Orthosiphon aristatus is a medicinal plant with possible potential beneficial effects on various metabolic disorders. This study aims to investigate the in vitro inhibitory effects of O. stamineus on hepatic fat accumulation and to further use the computational systems pharmacology approach to identify the pharmacokinetic properties of the bioactive compounds of O. stamineus and to predict their molecular mechanisms against NAFLD. Methods: The effects of an ethanolic extract of O. stamineus leaves on cytotoxicity, fat accumulation and antioxidant activity were assessed using HepG2 cells. The bioactive compounds of O. stamineus were identified using LC/MS and two bioinformatics databases, namely the Traditional Chinese Medicine Integrated Database (TCMID) and the Bioinformatics Analysis Tool for the Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM). Pathway enrichment analysis was performed on the predicted targets of the bioactive compounds to provide a systematic overview of the molecular mechanism of action, while molecular docking was used to validate the predicted targets. Results: A total of 27 bioactive compounds corresponding to 50 potential NAFLD-related targets were identified. O. stamineus exerts its anti-NAFLD effects by modulating a variety of cellular processes, including oxidative stress, mitochondrial β-oxidation, inflammatory signalling pathways, insulin signalling, and fatty acid homeostasis pathways. O. stamineus is significantly targeting many oxidative stress regulators, including JNK, mammalian target of rapamycin (mTOR), NFKB1, PPAR, and AKT1. Molecular docking analysis confirmed the expected high affinity for the potential targets, while the in vitro assay indicates the ability of O. stamineus to inhibit hepatic fat accumulation. Conclusion: Using the computational systems pharmacology approach, the potentially beneficial effect of O. stamineus in NAFLD was indicated through the combination of multiple compounds, multiple targets, and multicellular components.     

A case of sudden cardiac death due to mitochondrial disease

A 25-year-old, emaciated man without medical treatment was found to have died suddenly at home by his mother. At autopsy, there were no injuries to his body, but significant circulatory insufficiency was observed. Electron microscopy revealed abnormal mitochondria in cells of the cardiac conduction system. The conduction system was filled with mitochondrial size abnormalities and mitochondrial cristae abnormalities. No notable abnormal findings were observed in other organs. Genetic examination of the blood revealed the mitochondrial pathogenetic variant m.3243A>G. Epileptic seizures, diabetic ketoacidosis, and hyperosmolar hyperglycemic state were unlikely to be the cause of sudden death. The cause of death was diagnosed as arrhythmia possibly induced by the failure of the cardiac conduction system due to mitochondrial disease. This is a rare case of sudden death caused by an accumulation of abnormal mitochondria in the cardiac conduction system.     

Clinical characteristics of pediatric patients with COVID-19 between Omicron era vs. pre-Omicron era

IntroductionDetailed data on clinical characteristics in children with the omicron strain of SARS-COV-2 are limited.MethodsWe conducted a retrospective observational study of children with COVID-19 at the National Center for Child Health and Development to evaluate the clinical manifestations during and before the emergence of the omicron variant. Only symptomatic patients without underlying diseases were included. Participants were divided into two temporal groups: the “omicron era” (1/2022–2/2022) and the “pre-omicron era,” where the delta variant predominated (7/2021–11/2021). The patients were subclassified into an older vaccine-eligible group (aged 12–17 years), a younger vaccine-eligible group (aged 5–11 years), and a vaccine-ineligible group (aged 0–4 years).ResultsWe compared 113 patients in the omicron era with 106 in the pre-omicron era. Most patients in both eras had non-severe disease, and no patients required mechanical ventilation or died. Among patients aged 0–4 years, sore throat and hoarseness were more common during the omicron era than the pre-omicron era (11.1% vs. 0.0% and 11.1% vs. 1.5%, respectively). Croup syndrome was diagnosed in all patients with hoarseness. Among patients aged 5–11 years, vomiting was more frequent during the omicron era (47.2%) than during the pre-omicron era (21.7%). Cough and rhinorrhea were less common during the omicron era in patients aged 0–4 and 5–11 years, respectively, than during the pre-omicron era.ConclusionsIn children with COVID-19, clinical manifestations differed between the omicron and pre-omicron eras. In the Omicron era, croup syndrome was more frequent in vaccine-ineligible children.     

Effectiveness and Safety of Inhaled Antibiotics in Patients With Chronic Obstructive Pulmonary Disease. A Multicentre Observational Study

BackgroundWe aimed to describe the effectiveness and safety of inhaled antibiotics in chronic obstructive pulmonary disease (COPD) patients, as well as the patient profile in which they are usually prescribed and the patient groups that can most benefit from this treatment.MethodsMulticentre retrospective observational cohort study in COPD patients who had received ≥1 dose of inhaled antibiotics in the last 5 years. Clinical data from the two years prior to and subsequent to the start of the treatment were compared. Primary outcome: COPD exacerbations. Secondary outcomes: side effects, symptomatology (sputum purulence, dyspnoea), microbiological profile and pathogen eradication.ResultsOf 693 COPD patients analyzed (aged 74.1; 86.3% men; mean FEV₁ = 43.7%), 71.7% had bronchiectasis and 46.6% presented chronic bronchial infection (CBI) by Pseudomonas aeruginosa (PA). After 1 year of treatment with inhaled antibiotics, there was a significant decrease in the number of exacerbations (?33.3%; P < .001), hospital admissions (?33.3%; P < .001) and hospitalization days (?26.2%; P = .003). We found no difference in effectiveness between patients with or without associated bronchiectasis. Positive patient outcomes were more pronounced in PA-eradicated patients. We found a significant reduction in daily expectoration (?33.1%; P = .024), mucopurulent/purulent sputum (?53.9%; P < .001), isolation of any potentially pathogenic microorganisms (PPM) (?16.7%; P < .001), CBI by any PPM (?37.4%; P < .001) and CBI by PA (?49.8%; P < .001). CBI by any PPM and ≥three previous exacerbations were associated with a better treatment response. 25.4% of patients presented non-severe side-effects, the most frequent of these being bronchospasm (10.5%), dyspnoea (8.8%) and cough (1.7%).ConclusionsIn COPD patients with multiple exacerbations and/or CBI by any PPM (especially PA), inhaled antibiotics appear to be an effective and safe treatment, regardless of the presence of bronchiectasis.     

Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.