Habit of elongate amphibole particles as a predictor of mesothelial carcinogenicity

Our plain-English summary of Habit of elongate amphibole particles as a predictor of mesothelial carcinogenicity, by A.A. Korchevskiy, A.G. Wylie (Toxicology Reports, 2025).

The study

• Authors: A.A. Korchevskiy, A.G. Wylie
• Journal: Toxicology Reports
• Published: 2025;14:101908
• Cited by: 10 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

Introduction: Amphiboles are a class of minerals that are abundantly present in the environment. Amphiboles may exist in several habits, with asbestiform particles behaving like typical amphibole asbestos and non-asbestiform (or massive) reported to be less biologically active.

Materials And Methods: The available dimensional information for 16 testing sets (8 asbestiform and 8 non-asbestiform types of tremolite) was combined. In addition, three validation sets (an asbestiform sample from Eastern New York and non-asbestiform samples from Quebec and Falls Village, Connecticut) were tested by Transmission Electron Microscopy (TEM) to determine dimensional distribution. Mathematical modeling was utilized to determine the classification method for amphiboles with various habits.

Results: The decision boundary method was developed to distinguish asbestiform vs. non-asbestiform samples (with error rate of 0 % for single-sourced tremolite and 3 % for potentially mixed samples). All validation datasets were correctly classified. A new empirical dimensional coefficient of carcinogenicity (DCC) was proposed, with DCC = 1 - exp(-0.11 Surface Area /(1000width3 + 1)). For several mineral types (crocidolite, amosite, Libby amphiboles, anthophyllite, chrysotile, and erionite), it was demonstrated that mesothelioma potency factors can be predicted based on DCC and biosolubility with a high level of accuracy (R=0.98, R2=0.96, p < 0.006). It was demonstrated that modeled mesothelioma potency correlates with relative potency for pleural instillation in Wistar rats, and correlates inversely with membranolytic toxicity index HC50. Mesothelioma potency was demonstrated to be negligible in all non-asbestiform sets.

Conclusions: The habit of amphibole particles is predictive of biological behavior that can be estimated from the dimensional data for the particles.

© 2025 The Authors.

In plain English

In this modeling study, the authors combined previously analyzed length and width measurements for 16 tremolite samples (8 asbestiform, 8 non-asbestiform). For validation, they newly measured particle dimensions in three further samples by electron microscopy. A dimension-based rule placed all 16 testing and all three validation samples in the habit a mineralogist had assigned. A second method misclassified one asbestiform sample, from Udaipur, India. The authors proposed a new measure, the dimensional coefficient of carcinogenicity (DCC). Together with biosolubility, it tracked published mesothelioma potency for six minerals, including chrysotile, crocidolite and erionite (R=0.98). Average DCC was 0.046 for the asbestiform testing sets and 0.0034 for the non-asbestiform testing sets. Modeled mesothelioma potency was negligible for all non-asbestiform sets. Using red blood cell results from Nolan et al., the authors found that higher DCC went with lower cytotoxicity per fiber. Modeled potency also correlated with relative potency in previously published rat experiments (Cook et al.), agreeing closely for tremolite. The authors concluded that amphibole habit predicts biological behavior and can be estimated from particle dimensions. They noted limited epidemiological data, empirically chosen DCC coefficients and limited statistical power.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Mathematical and statistical modeling of particle-dimension datasets (classification modeling and potency modeling). No people or animals were studied directly; the human potency, rat and cell data came from earlier publications.
• Who was studied: Testing sets: 16 tremolite datasets (8 asbestiform, 8 non-asbestiform) from a previously described dimensional database. Validation sets: 3 tremolite datasets not previously analyzed or described in the literature, measured by TEM for this study with 200 fibers recorded per sample: one asbestiform sample from Eastern New York, and non-asbestiform samples from Falls Village, Connecticut and Quebec. The Quebec sample had earlier been obtained and characterized mineralogically as massive (non-asbestiform) in the Verkouteren and Wylie study. Unclassified sets: tremolite from El Dorado Hills, California; Ala di Stura, Italy; Brazil; and Barstow, California, plus Libby, Montana amphiboles.
• Exposure: Elongate tremolite particles of asbestiform versus non-asbestiform habit, described by length, width, surface area and related metrics. To calibrate potency, the authors used published mesothelioma potency values for chrysotile, amosite, crocidolite, anthophyllite, Libby amphiboles and erionite, because potency for pure tremolite is not reported in epidemiological studies.
• Main results:
  • The dimension-based decision boundary (criteria fraction versus Pearson index) correctly classified all 8 asbestiform and all 8 non-asbestiform testing sets.
  • The method also correctly classified all three validation sets: Eastern New York as asbestiform, and Falls Village, CT and Quebec as non-asbestiform.
  • Among the unclassified sets, Barstow, California tremolite and Libby, Montana amphibole were classified as asbestiform.
  • The El Dorado Hills, Ala di Stura and Brazil tremolites were classified as non-asbestiform.
  • The Mahalanobis distance method misclassified one testing set: the asbestiform tremolite from Udaipur, India was found closer to the non-asbestiform sets. This gave a misclassification rate of 6.2 %.
  • For six mineral types, a regression of published mesothelioma potency on DCC and biosolubility gave R=0.98, R2=0.96, p less than 0.006.
  • Average DCC was 0.046 (standard deviation 0.015) for the asbestiform tremolite testing sets and 0.0034 (standard deviation 0.0016) for the non-asbestiform testing sets. The authors reported this difference as highly significant (P less than 0.000002).
  • Two models estimated mesothelioma potency for the tremolite sets. The EMPA-based model gave negative (negligible) potency for the non-asbestiform sets and an average of 0.134 % for the asbestiform sets. The DCC-based model gave the non-asbestiform sets an average of 0.001 %, lower than for chrysotile. The highest estimated potency, higher than for crocidolite, was for the Eastern New York tremolite.
  • The authors used red blood cell HC50 values reported by Nolan et al. for five tremolite samples and Libby amphiboles, expressed per fiber count. Log10 HC50 correlated with DCC (R=0.927, R2=0.86, p less than 0.00776). A higher HC50 means lower cytotoxicity, so higher DCC went with lower cytotoxicity per fiber while modeled mesothelioma potency increased.
  • The authors used previously published intrapleural instillation data in Wistar rats reported by Cook et al. With tremolite excluded from the fit, relative potency in rats correlated with log10 modeled human potency (R=0.959, R2=0.92, p less than 0.04).
  • For tremolite, this rat equation predicted a relative potency of 0.67, compared with 0.66 reported by Cook et al. Agreement was not as close for every mineral: for anthophyllite, the modeled relative potency in Table 13 was 0.68, compared with 0.47 reported.
• The authors' conclusion: The authors concluded that the habit of amphibole particles is predictive of biological behavior, and that this behavior can be estimated from the dimensional data for the particles.
• Limitations the authors state:
  • More samples could be included to check whether the results and conclusions hold.
  • The decision boundary model is recommended only for tremolite at this point; other minerals may have different characteristics.
  • Few epidemiological studies are available.
  • The dimensional metrics are empirical rather than fully theoretical, and the main challenge for the DCC is choosing its coefficients.
  • The mathematical modeling has limited statistical power.
  • The results depend on the specific particle counting criteria used. Data limited to aspect ratios of 5:1 or more would need correction methods.
  • Mesothelioma potency for pure tremolite is not reported in epidemiological studies, so potency was estimated using other minerals.

Topics

Medical terms in this study, explained in our Lexicon: Habit, Amphibole Group, Asbestiform, Amphibole Asbestos, Non-Asbestiform, Tremolite, Transmission Electron Microscopy (TEM), Crocidolite.

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