Dataset Information

Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.

ABSTRACT: Around nine million people have been exposed to toxic humidifier disinfectants (HDs) in Korea. HD exposure may lead to HD-associated lung injuries (HDLI). However, many people who have claimed that they experienced HD exposure were not diagnosed with HDLI but still felt discomfort, possibly due to the unknown effects of HD. Therefore, this study examined HD-exposed subjects with normal-appearing lungs, as well as unexposed subjects, in clusters (subgroups) with distinct characteristics, classified by deep-learning-derived computed-tomography (CT)-based tissue pattern latent traits. Among the major clusters, cluster 0 (C0) and cluster 5 (C5) were dominated by HD-exposed and unexposed subjects, respectively. C0 was characterized by features attributable to lung inflammation or fibrosis in contrast with C5. The computational fluid and particle dynamics (CFPD) analysis suggested that the smaller airway sizes observed in the C0 subjects led to greater airway resistance and particle deposition in the airways. Accordingly, women appeared more vulnerable to HD-associated lung abnormalities than men.

SUBMITTER: Li F

PROVIDER: S-EPMC9565839 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Publications

Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.

Li Frank F Choi Jiwoong J Zhang Xuan X Rajaraman Prathish K PK Lee Chang-Hyun CH Ko Hongseok H Chae Kum-Ju KJ Park Eun-Kee EK Comellas Alejandro P AP Hoffman Eric A EA Lin Ching-Long CL

International journal of environmental research and public health 20220920 19

Around nine million people have been exposed to toxic humidifier disinfectants (HDs) in Korea. HD exposure may lead to HD-associated lung injuries (HDLI). However, many people who have claimed that they experienced HD exposure were not diagnosed with HDLI but still felt discomfort, possibly due to the unknown effects of HD. Therefore, this study examined HD-exposed subjects with normal-appearing lungs, as well as unexposed subjects, in clusters (subgroups) with distinct characteristics, classifi ...[more]

PMID: 36231196

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Project description:BackgroundLung disease caused by exposure to chemical substances such as polyhexamethylene guanidine (PHMG) used in humidifier disinfectants (HDs) has been identified in Korea. Several researchers reported that exposure classification using a questionnaire might not correlate with the clinical severity classes determined through clinical diagnosis. It was asserted that the lack of correlation was due to misclassification in the exposure assessment due to recall bias. We identified the cause of uncertainty to recognize the limitations of differences between exposure assessment and clinical outcomes assumed to be true value. Therefore, it was intended to check the availability of survey using questionnaires and required to reduce misclassification error/bias in exposure assessment.MethodsHDs exposure assessment was conducted as a face-to-face interview, using a questionnaire. A total of 5245 applicants participated in the exposure assessment survey. The questionnaire included information on sociodemographic and exposure characteristics such as the period, frequency, and daily usage amount of HDs. Based on clinical diagnosis, a 4 × 4 cross-tabulation of exposure and clinical classification was constructed. When the values of the exposure rating minus the clinical class were ≥ 2 and ≤ - 2, we assigned the cases to the overestimation and underestimation groups, respectively.ResultsThe sex ratio was similar in the overestimation and underestimation groups. In terms of age, in the overestimation group, 90 subjects (24.7%) were under the age of 10, followed by 52 subjects (14.2%) in their 50s. In the underestimation group, 195 subjects (56.7%) were under the age of 10, followed by 80 subjects (23.3%) in their 30s. The overestimation group may have already recovered and responded excessively due to psychological anxiety or to receive compensation. However, relatively high mortality rates and surrogate responses observed among those under 10 years of age may have resulted in inaccurate exposure in the underestimation group.ConclusionsHDs exposure assessment using a questionnaire might not correlate with adverse health effects due to recall bias and various other causes such as recovery of injury and psychological anxiety. This study revealed exposure misclassification and characteristics affected by HDs and proposed a questionnaire-based exposure assessment methodology to overcome the limitations of past exposure assessment.

Project description:BackgroundWalnuts are grown worldwide in temperate areas and producers are facing an increasing demand. In a climate change context, the industry also needs cultivars that provide fruits of quality. This quality includes satisfactory filling ratio, thicker shell, ease of cracking, smooth shell and round-shaped walnut, and larger nut size. These desirable traits have been analysed so far using calipers or micrometers, but it takes a lot of time and requires the destruction of the sample. A challenge to take up is to develop an accurate, fast and non-destructive method for quality-related and morphometric trait measurements of walnuts, that are used to characterize new cultivars or collections in any germplasm management process.ResultsIn this study, we develop a method to measure different morphological traits on several walnuts simultaneously such as morphometric traits (nut length, nut face and profile diameters), traits that previously required opening the nut (shell thickness, kernel volume and filling kernel/nut ratio) and traits that previously were difficult to quantify (shell rugosity, nut sphericity, nut surface area and nut shape). These measurements were obtained from reconstructed 3D images acquired by X-ray computed tomography (CT). A workflow was created including several steps: noise elimination, walnut individualization, properties extraction and quantification of the different parts of the fruit. This method was applied to characterize 50 walnuts of a part of the INRAE walnut germplasm collection made of 161 unique accessions, obtained from the 2018 harvest. Our results indicate that 50 walnuts are sufficient to phenotype the fruit quality of one accession using X-ray CT and to find correlations between the morphometric traits. Our imaging workflow is suitable for any walnut size or shape and provides new and more accurate measurements.ConclusionsThe fast and accurate measurement of quantitative traits is of utmost importance to conduct quantitative genetic analyses or cultivar characterization. Our imaging workflow is well adapted for accurate phenotypic characterization of a various range of traits and could be easily applied to other important nut crops.

Dataset Information

Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.

Publications

Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.

Similar Datasets

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