ArticleAtmospheric measurement techniques2017
An online monitor of the oxidative capacity of aerosols (o-MOCA).
Article in Atmospheric measurement techniques, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 40 citations in OpenAlex.
- Development and Validation of the Particle into Nitroxide Quencher System with BPEAnit Probe for High-Sensitivity Reactive Oxygen Species Detection in Atmospheric Monitoring.Sensors (Basel, Switzerland) · 2025Article
- The Oxidative Potential of Airborne Particulate Matter Research Trends, Challenges, and Future Perspectives-Insights from a Bibliometric Analysis and Scoping Review.Antioxidants (Basel, Switzerland) · 2024Article
- Measurements of Oxidative Potential of Particulate Matter at Belgrade Tunnel; Comparison of BPEAnit, DTT and DCFH Assays.International journal of environmental research and public health · 2019Article
- Application of a Fluorescent Probe for the Online Measurement of PM-Bound Reactive Oxygen Species in Chamber and Ambient Studies.Sensors (Basel, Switzerland) · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The capacity of airborne particulate matter to generate reactive oxygen species (ROS) has been correlated with the generation of oxidative stress both in vitro and in vivo. The cellular damage from oxidative stress, and by implication with ROS, is associated with several common diseases, such as asthma and chronic obstructive pulmonary disease (COPD), and some neurological diseases. Yet currently available chemical and in vitro assays to determine the oxidative capacity of ambient particles require large samples, analyses are typically done offline, and the results are not immediate. Here we report the development of an online monitor of the oxidative capacity of aerosols (o-MOCA) to provide online, time-resolved assessment of the capacity of airborne particles to generate ROS. Our approach combines the Liquid Spot Sampler (LSS), which collects particles directly into small volumes of liquid, and a chemical module optimized for online measurement of the oxidative capacity of aerosol using the dithiothreitol (DTT) assay. The LSS uses a three-stage, laminar-flow water condensation approach to enable the collection of particles as small as 5 nm into liquid. The DTT assay has been improved to allow the online, time-resolved analysis of samples collected with the LSS but could be adapted to other collection methods or offline analysis of liquid extracts. The o-MOCA was optimized and its performance evaluated using the 9,10-phenanthraquinone (PQ) as a standard redox-active compound. Laboratory testing shows minimum interferences or carryover between consecutive samples, low blanks, and a reproducible, linear response between the DTT consumption rate (nmol min
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.