Exposure to ambient air particulate matter (PM) is well established as a risk factor for cardiovascular and pulmonary disease. Both epidemiologic and controlled exposure studies in humans and animals have demonstrated an association between air pollution exposure and metabolic disorders such as diabetes. Given the central role of the liver in peripheral glucose homeostasis, we exposed mice to filtered air or PM for 16 weeks and examined its effect on hepatic metabolic pathways using stable isotope resolved metabolomics (SIRM) following a bolus of C-glucose. Livers were analyzed for the incorporation of C into different metabolic pools by IC-FTMS or GC-MS. The relative abundance of C-glycolytic intermediates was reduced, suggesting attenuated glycolysis, a feature found in diabetes. Decreased C-Krebs cycle intermediates suggested that PM exposure led to a reduction in the Krebs cycle capacity. In contrast to decreased glycolysis, we observed an increase in the oxidative branch of the pentose phosphate pathway and C incorporations suggestive of enhanced capacity for the de novo synthesis of fatty acids. To our knowledge, this is one of the first studies to examine C-glucose utilization in the liver following PM exposure, prior to the onset of insulin resistance (IR).

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874681PMC
http://dx.doi.org/10.1038/s41598-019-53716-yDOI Listing

Publication Analysis

Top Keywords

particulate matter
8
krebs cycle
8
exposure
5
air
4
air pollution-derived
4
pollution-derived particulate
4
matter dysregulates
4
dysregulates hepatic
4
hepatic krebs
4
cycle glucose
4

Similar Publications

With rapid, energy-intensive, and coal-fueled economic growth, global air quality is deteriorating, and particulate matter pollution has emerged as one of the major public health problems worldwide. It is extremely urgent to achieve carbon emission reduction and air pollution prevention and control, aiming at the common problem of weak and unstable signals of characteristic elements in the application of laser-induced breakdown spectroscopy (LIBS) technology for trace element detection. In this study, the influence of the optical fiber collimation signal enhancement method on the LIBS signal was explored.

View Article and Find Full Text PDF

Aim: Air pollution remains the single largest environmental health risk factor, while atrial fibrillation (AF) is the most prevalent arrhythmia globally. The study aimed to investigate the relationship between short-term exposure to air pollution and acute AF admissions.

Methods: Individual data on AF hospitalization in the years 2011-2020 were collected from the National Health Fund in Poland (ICD-10: I48.

View Article and Find Full Text PDF

The role of mTOR activation in steroid-resistant asthma: insights from particulate matter-induced mouse model and patient studies.

Inflamm Res

January 2025

Institute of Allergy and Clinical Immunology, Biomedical Research Institute, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea.

Particulate matter (PM) exposure has been proposed as one of the causes of steroid resistance. However, studies investigating this using patient samples or animals are still lacking. Therefore, in this study, we aimed to investigate the changes in cytokines and mTOR (mammalian target of rapamycin) activation in patients with steroid resistant asthma and the role of mTOR in a mouse model of steroid resistant asthma induced by PM.

View Article and Find Full Text PDF

Introduction: Exposure to environmental factors ( air pollution and second-hand tobacco smoke) have been associated with impaired lung function. However, the impact of environmental factors on lung health is usually evaluated separately and not with an exposomic framework. In this regard, breath analysis could be a noninvasive tool for biomonitoring of global human environmental exposure.

View Article and Find Full Text PDF

Background: Environmental exposures such as airborne pollutant exposures and socio-economic indicators are increasingly recognized as important to consider when conducting clinical research using electronic health record (EHR) data or other sources of clinical data such as survey data. While numerous public sources of geospatial and spatiotemporal data are available to support such research, the data are challenging to work with due to inconsistencies in file formats and spatiotemporal resolutions, computational challenges with large file sizes, and a lack of tools for patient- or subject-level data integration.

Results: We developed FHIR PIT (HL7® Fast Healthcare Interoperability Resources Patient data Integration Tool) as an open-source, modular, data-integration software pipeline that consumes EHR data in FHIR® format and integrates the data at the level of the patient or subject with environmental exposures data of varying spatiotemporal resolutions and file formats.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!