Individual exposure of ambient particulate matters and eosinophilic chronic rhinosinusitis with nasal Polyps: Dose-Response, mediation effects and recurrence prediction

Wang, Jiajia; Shen, Shen; Yan, Bing; He, Yunsheng; Zhang, Guoji; Shan, Chunguang; Yang, Qintai; Qin, Long; Duan, Zhijian; Jiang, Luyun; Wang, Xin; Wei, Xin; Chen, Rui; Zhang, Luo

doi:10.1016/j.envint.2023.108031

Cited by 5 publications

(2 citation statements)

References 39 publications

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“…The dataset captured well the spatial variability of PM 2.5 concentrations in China, with high prediction accuracy (CV-R 2 between 0.86 and 0.90) and strong predictive power (R 2 between 0.80 and 0.82). This dataset has been increasingly used in research focusing on public health, ecological quality, air pollution, and so forth (Feng et al, 2023; Jiang et al, 2023; Wang et al, 2023).…”

Section: Methodsmentioning

confidence: 99%

Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model

Duan,

Cao,

Wang

et al. 2024

Progress in Physical Geography: Earth and Environment

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Fine particulate matter (PM2.5) is a major source of air pollution and exerts serious impacts on human health. The 3D urban landscape patterns can significantly affect the diffusion and emissions of PM2.5. However, studies on the relationships between 3D urban landscape patterns and PM2.5 pollution across different seasons remain understudied. With the ground-level air pollutants estimated by the remote sensing and fine-scale building information, this study applied the multiscale geographically weighted regression model to explore such relationships. Wuhan, the largest metropolis in Central China, was selected as the study area for the application of our methodology. The results showed that the direction, degree, and scale of the effect of 3D urban landscape patterns on PM2.5 pollution varied across seasons. For building height, the standard deviation of building height had a significant positive correlation with PM2.5 all year round. For building density, the building count density showed a significant positive correlation with PM2.5 in general, with the bandwidth in winter and autumn smaller than in spring and summer. The building plan area fraction exerted both positive and negative influences on PM2.5, dependent on season and location. The bandwidth of it gradually increased from spring to winter, with the effect changing from local to regional scale. For building volume, the floor area ratio showed a significant negative correlation with PM2.5 in winter and autumn, and a localized effect was found, especially in winter. The findings of this study provide practical implications for urban planning and policy making to mitigate PM2.5 pollution in the rapidly urbanizing regions.

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Section: Methodsmentioning

confidence: 99%

Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model

Duan,

Cao,

Wang

et al. 2024

Progress in Physical Geography: Earth and Environment

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“…All extrinsic environmental factors can damage this epithelial barrier in CRS patients due to decreased expression of the tight junction proteins occludin-1, zonula occludens 1 [36], E-cadherin [37], and claudin-1 [38], resulting in a hyperreactive immune response [39]. Recent epidemiological evidence suggested an effect of ambient pollutants, such as particulate matter PM 10 and PM 2.5 , on eosinophil recruitment, which could stimulate CRS establishment or be involved in already existing CRS progression [40].…”

Section: Barrier Disruption-role Of the Epitheliummentioning

confidence: 99%

Targeting Epithelium Dysfunction and Impaired Nasal Biofilms to Treat Immunological, Functional, and Structural Abnormalities of Chronic Rhinosinusitis

Petalas

Goudakos

Konstantinou

2023

IJMS

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Chronic rhinosinusitis (CRS) with (CRSwNP) or without (CRSsNP) nasal polyps is a prevalent and heterogeneous disorder existing as a spectrum of clinical conditions with complex underlying pathomechanisms. CRS comprises a broad syndrome characterized by multiple immunological features involving complex interactions between the genes, the microbiome, host- and microbiota-derived exosomes, the epithelial barrier, and environmental and micromilieu exposures. The main pathophysiological feature is an epithelial barrier disruption, accompanied by microbiome alterations and unpredictable and multifactorial immunologic overreactions. Extrinsic pathogens and irritants interact with multiple epithelial receptors, which show distinct expression patterns, activate numerous signaling pathways, and lead to diverse antipathogen responses. CRSsNP is mainly characterized by fibrosis and mild inflammation and is often associated with Th1 or Th17 immunological profiles. CRSwNP appears to be associated with moderate or severe type 2 (T2) or Th2 eosinophilic inflammation. The diagnosis is based on clinical, endoscopic, and imaging findings. Possible CRS biomarkers from the peripheral blood, nasal secretions, tissue biopsies, and nasally exhaled air are studied to subgroup different CRS endotypes. The primary goal of CRS management is to maintain clinical control by nasal douching with isotonic or hypertonic saline solutions, administration of nasal and systemic steroids, antibiotics, biologic agents, or, in persistent and more severe cases, appropriate surgical procedures.

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Development and Validation of an Explainable Prediction Model for Postoperative Recurrence in Pediatric Chronic Rhinosinusitis

Jiang,

Qi,

Xie

et al. 2024

Otolaryngol.--head neck surg.

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ObjectiveThis study aims to develop an interpretable machine learning (ML) predictive model to assess its efficacy in predicting postoperative recurrence in pediatric chronic rhinosinusitis (CRS).Study DesignA decision analysis was performed with retrospective clinical data.SettingRecurrent group and nonrecurrent group.MethodsThis retrospective study included 148 pediatric CRS treated with functional endoscopic sinus surgery from January 2015 to January 2022. We collected demographic characteristics and peripheral blood inflammatory indices, and calculated inflammation indices. Models were trained with 3 ML algorithms and compared their predictive performance using the area under the receiver operating characteristic (AUC) curve. Shapley Additive Explanations and Ceteris Paribus profiles were used for model interpretation. The final model was transformed into a web for interactive visualization.ResultsAmong the 3 ML models, the Random Forest (RF) model demonstrated the best discriminative ability (AUC = 0.728). After reducing features based on importance and tuning parameters, the final RF model, including 4 features (systemic immune inflammation index (SII), pan‐immune‐inflammation value (PIV) and percentage of eosinophils (E%) and lymphocytes (L%)), showed good predictive performance in internal validation (AUC = 0.779). Global interpretation of the model suggested that L% and E% substantially contribute to the overall model. Local interpretation revealed a nonlinear relationship between the included features and model predictions. To enhance its clinical utility, the model was converted into a web (https://juice153.shinyapps.io/CRSRecurrencePrediction/).ConclusionOur ML model demonstrated promising accuracy in predicting postoperative recurrence in pediatric CRS, revealing a complex nonlinear relationship between postoperative recurrence and the features SII, PIV, L%, and E%.

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Individual exposure of ambient particulate matters and eosinophilic chronic rhinosinusitis with nasal Polyps: Dose-Response, mediation effects and recurrence prediction

Cited by 5 publications

References 39 publications

Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model

Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model

Targeting Epithelium Dysfunction and Impaired Nasal Biofilms to Treat Immunological, Functional, and Structural Abnormalities of Chronic Rhinosinusitis

Development and Validation of an Explainable Prediction Model for Postoperative Recurrence in Pediatric Chronic Rhinosinusitis

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Individual exposure of ambient particulate matters and eosinophilic chronic rhinosinusitis with nasal Polyps: Dose-Response, mediation effects and recurrence prediction

Cited by 5 publications

References 39 publications

Exploring the relationships between 3D urban landscape patterns and PM2.5 pollution using the multiscale geographic weighted regression model

Exploring the relationships between 3D urban landscape patterns and PM2.5 pollution using the multiscale geographic weighted regression model

Targeting Epithelium Dysfunction and Impaired Nasal Biofilms to Treat Immunological, Functional, and Structural Abnormalities of Chronic Rhinosinusitis

Development and Validation of an Explainable Prediction Model for Postoperative Recurrence in Pediatric Chronic Rhinosinusitis

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Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model

Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model