OBJECTIVE
The component‑specific toxicity of fine particulate matter (PM2.5) and the underlying metabolic pathways driving airflow impairment in chronic obstructive pulmonary disease (COPD) remain unclear. We evaluated how specific PM2.5 constituents alter circulating metabolites and mediate short‑term changes in peak expiratory flow (PEF) among COPD patients.
METHODS
A panel study was conducted in 32 patients with stable COPD in Beijing (2018-2019). Participants were followed-up across four seasons, yielding 3363 daily PEF measurements and 208 serum samples for untargeted metabolomics. PM2.5 components concentrations were obtained from a high-resolution (1 km) dataset integrating ground observations, satellite retrievals, and model simulations. Linear mixed-effects models were used to estimate the associations between PM2.5 components and PEF, and a meet-in-the-middle strategy was adopted to identify mediating metabolites and pathways.
RESULTS
PEF declines were associated with interquartile range increase in several PM2.5 components (lag0-7 days moving average), most notably for black carbon [-5.88 (-8.76 ~ -3.01) L/min] and sulfate [-4.78 (-8.82 ~ -0.73) L/min]. Metabolomic analysis identified 12 metabolites significantly linked to PEF (q < 0.05). Pathway enrichment highlighted urea cycle/amino group metabolism (P = 0.041) and bile acid biosynthesis (P = 0.012) as key biological response routes. Five metabolites were identified as mediators of the associations between PM2.5 components and PEF, notably Nb-arachidoyltryptamine and 6-nitrochrysene.
CONCLUSION
These findings highlight black carbon and sulfate as primary drivers of PM2.5-related lung function impairment in COPD patients, likely acting through systemic metabolic perturbations. Our study supports targeted emission controls and suggests metabolic profiling as a potential approach for targeted prevention in vulnerable populations.
Jiachen Li, Lirong Liang, Y. Cai et al.· Respiratory Research· 0 citations
Mesoscale convective systems (MCSs) are key drivers of the hydrological cycle over High Mountain Asia (HMA), delivering essential warm-season rainfall but also triggering flash floods and landslides. Their simulation over this complex region remains challenging for coarse-resolution models, and regional convection-permitting models cannot fully capture large-scale feedback. In this two-part study, we use global models at 25-km and 3-km resolution (the latter storm-resolving) to assess MCS characteristics and climate response over HMA. Part 1 provides a comprehensive evaluation against satellite observations. Both models capture the spatial distribution and seasonality of MCSs but overestimate warm-season frequency, with underestimation at low elevations and overestimation at high elevations. The storm-resolving model better reproduces the diurnal cycle. At the event scale, simulated MCSs are slightly larger, longer-lived, and more intense than observed. Both reproduce the dominant eastward propagation and speeds, but exaggerate a secondary southwestward mode. They capture broad precipitation patterns, including the dry zone north of the Himalayas, though the 25-km model retains a wet bias along the southern slopes that is reduced in the 3-km simulation. These findings highlight both the promise and limitations of current high-resolution global models in representing MCSs over complex terrain, providing a basis for assessing historical and future changes (Part 2) and guiding future model development.
W. Dong, Deliang Chen, Xiaomeng Huang et al.· Journal of Climate· 0 citations
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