Fingerprinting the effect of airborne particulate matter via in vitro toxicoproteomics
Bibliographic record
Abstract
It is a challenge to assess the toxicity of environmental air particulate matter (PM) because PM composition is complex and variable, due to source contribution and atmospheric transformation. The goal of this study is to establish an in vitro model that can fingerprint the cytotoxic effects of airborne PM and their associated toxicity mechanisms. For this purpose, the cytotoxic effects of different reference and environmental particles on A549 human lung epithelial cells were characterized using multiple endpoint assays (cytokine release, LDH release, BrdU incorporation, cellular ATP and resazurin reduction) and proteomic analyses (2D-GE and MALDI-TOF-TOF-MS/MS). The results of this study demonstrated that proteomic analyses can distinguish the influences of different (carbon black and titanium dioxide) and similar (cristobalite and α-quartz) particles on various pathways in A549 cells (e.g., cell death and cell proliferation); and the cytotoxicity assays were capable of differentiating the phenotypic outcomes of the particles, which were complementary and supportive to pathway analyses. The ability of in vitro toxicoproteomics to differentiate the toxicity of environmental particles was tested on Ottawa urban dust (EHC-93) and its water-insoluble and soluble fractions. Findings from both cytotoxicity assays and proteomic analyses consistently indicated that the insoluble materials explained most of the toxic effects of the total PM. Interestingly, the toxic potency of EHC-93 total was not equal to the sum of its insoluble and soluble fractions, implying inter-component interactions between insoluble and soluble materials that may be reflected through synergistic or antagonistic in vitro responses. The insoluble and soluble fractions uniquely altered the expression patterns of the proteins involved in pathways such as cell death, cell proliferation and inflammation. For example, the insoluble and soluble fractions oppositely altered the expression of the proteins (e.g., TREM1, PDIA3, PKM and ENO1) involved in an inflammatory response pathway in A549 cells, and the insoluble fraction was more potent than the soluble fraction in increasing secretion of pro-inflammatory cytokines MCP-1 and IL-8 from A549 cells. In essence, in vitro toxicoproteomics is a valuable tool in relating the physicochemical characteristics of ambient air particles to their biological reactivity through understanding their mechanisms of toxicity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".