Geology Reports⌕ Search

USGS · 70232258

Demonstration of a novel quantitative microscopy technique for automated characterization of in situ particulate matter in coal miners with progressive massive fibrosis

Abstract

Rationale: Increasing exposure to respirable crystalline silica (RCS) linked to changes in mining production processes has been implicated in the resurgence of severe lung disease in U.S. coal miners. Lung mineralogy can provide insight into particle pathogenesis. However, standard approaches to characterizing in situ particulate matter (PM) by pulmonary pathologists have poor inter-rater comparability, and consensus agreement is time consuming. Scanning electron microscopy/energy-dispersive spectroscopy (SEM/EDX) is technically complex and labor intensive. We developed a method for quantitative in situ PM characterization using conventional polarized light microscopy (PLM) and explored PM features in lung tissue of coal miners with progressive massive fibrosis (PMF). Methods: With institutional review board approval, PLM images were obtained from 30 miners with PMF, classified by pathologists consensus based on PM profusion; 10 from each profusion group (mild/moderate/severe) were selected. Automated PM counting and characterization (including dimensions and grayscale intensity of PM > 0.3 m diameter) was performed on image samples using PLM with modified cell-counting software (BZ-X800 light microscope, Keyence Corporation, Osaka, Japan) (Figure 1). Quantitative PM density loge(PM count)/mm3 tissue was calculated for each sample and compared to pathologist PM profusion groups. PMF lesion type using consensus pathologist classification (13 coal-type, 9 mixed-type, and 8 silicotic-type) was compared to automated PM birefringence level (% particles with mean grayscale intensity <65, range 0-255). RCS particles are expected to be weakly birefringent (lower intensity) relative to other common minerals (e.g., silicates) contained in coal mine dust. PM features were analyzed in R 4.0.3 using one-way ANOVA for between-group comparisons. Results: Measured PM log-density increased significantly with higher qualitative profusion group (mild=10.480.98/mm3, moderate=11.460.81/mm3, severe=12.520.86/mm3, p<0.0001). Prevalence of weakly birefringent particles was significantly higher among silicotic-type PMF samples (31.57.9%) compared to either coal-type (21.510.1%, p=0.022) or mixed-type lesions (21.510.5%, p=0.025). Conclusion: This pilot study demonstrates the feasibility of a novel quantitative microscopy technique for counting and characterizing in situ lung PM in coal miners with PMF. Quantitative PM burden was comparable to pulmonary pathologists consensus profusion classification, but this method was substantially less time consuming and labor intensive and provided additional information about relevant PM features. The higher prevalence of weakly birefringent particles seen in silicotic-type PMF lesions may help inform mineralogic pathogenesis of RCS. Future efforts will expand the number of PMF cases analyzed, further validate our mineralogic findings using data from SEM/EDX and lung tissue digestate methods, and compare findings in historical versus contemporary coal miners with PMF.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Jeremy T. Hua, Lauren M. Zell-Baran, L. H. Go, Carlyne D. Cool, Heather A. Lowers, K. S. Almberg, Emily A. Sarver, Susan M. Majka, Kathy D. Pang, R. A. Cohen, Cecil S. Rose. 2022-05-02. Demonstration of a novel quantitative microscopy technique for automated characterization of in situ particulate matter in coal miners with progressive massive fibrosis. https://doi.org/10.1164/ajrccm-conference.2022.205.1_meetingabstracts.a2489

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Authoritative knowledge infrastructure for GeoAI: Implications for scientific spatial data providers

Geospatial Artificial Intelligence (GeoAI) increasingly relies on automated analysis of authoritative geospatial data, exposing limitations in data infrastructures originally designed for simple dissemination rather than for knowledge-driven use. From the perspective of scientific spatial data providers, the challenge is enabling GeoAI responsibly while retaining semantic clarity, provenance, reproducibility, and governance. This short paper (i) examines how GeoAI exposed limitations within existing geospatial data infrastructures, and (ii) identifies provider-side requirements for an authoritative knowledge infrastructure. Drawing on GIScience, scientific workflow, and operational AI literature, the paper outlines implications for national mapping organizations that seek to support advanced analytics without jeopardizing scientific rigor or stewardship responsibilities.

Conference Paper↗

Springs of the Catskill Mountains: A conduit flow system in predominantly siliciclastic strata

The Catskill Mountains of New York state are composed of thick sequences of interbedded mudstone, sandstone, and siltstone that are intercalated with thin beds of paludal limestone and calcareous mudstone. Sandstones often contain rip-up clasts of calcareous material at their bases and contain minor amounts of carbonate cement throughout their mass. This minor amount of calcareous material weathers out to produce thin zones of solutional porosity and permeability integrated within perched aquifers that feed perennial hillslope springs. Solutional features are evident within thin carbonate lenses and along fractures in sandstones, occasionally resulting in explorable cave-sized conduits. This study focuses on the behavior of bedrock springs and seeps in the headwaters of the Neversink River basin above the Neversink Reservoir. Bedrock springs are numerous throughout the Catskill Mountains and serve to provide baseflow to the headwater streams that tends to be more persistent during dry times than other baseflow sources. We observed dissolution-influenced conduits within the bedrock, and suffosional conduits within unconsolidated materials. Continuous water temperature at six springs was monitored at hourly intervals from May to October 2022 to investigate the thermal response of groundwater to daily and seasonal changes in air temperature along with event-based meteorological events. Temperature monitoring was augmented at some springs with time-lapse photography to evaluate persistence of flow. The thermal responses of springs to precipitation events were highly variable across sites, with some springs exhibiting flashy responses indicating a strong connection to the surface, while other springs showed muted or no thermal response to events. The seasonal thermal response also varied across sites having lag times of 23-48 days between peak air temperature and peak spring water temperature. The water temperatures and geochemical compositions of these bedrock springs support a conceptual model of multiple residence times, showing both event and seasonal groundwater storage within the conduit flow system that feeds the springs of the Catskill Mountains.

New York↗

Rapid deglaciation of the Tuolumne Meadows region linked to glacier hypsometry

During the LGM deglaciation (19–11 ka), episodes of glacier retreat and stabilization in the western United States are often attributed to abrupt climate change events via changes in Atlantic Meridional Overturning Circulation (e.g., Becker et al. 2025; McGee et al. 2018; Phillips 2016). However, there is considerable variability in the magnitude and timing of glacier retreat across the western US that is difficult to reconcile with a uniform climate forcing (Marcott et al. 2019), indicating either heterogeneous climate change or the influence of local non-climatic variables, such as glacier hypsometry (Young et al. 2011). Prior work from basal lake radiocarbon ages (Gillespie and Clark 2011) and cosmogenic nuclide dating (Phillips 2016; Phillips et al. 2009; Rood et al. 2011) established that Sierra Nevada glaciers receded from LGM moraines to north-facing cirques between 18 and 15 ka, with most deglaciation occurring at 15.8 ± 0.5 ka. As discussed above, geomorphic evidence supports abrupt glacier stagnation and in situ melting in the Tuolumne Meadows region.

Calfiornia↗