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Khajonklin T, Sun YM, Leon Guo YL, Hsu HI, Yoon CS, Lin CY, Tsai PJ. Utilizing Artificial Neural Networks for Establishing Hearing-Loss Predicting Models Based on a Longitudinal Dataset and Their Implications for Managing the Hearing Conservation Program. Saf Health Work 2024; 15:220-227. [PMID: 39035795 PMCID: PMC11255955 DOI: 10.1016/j.shaw.2024.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 02/02/2024] [Accepted: 02/18/2024] [Indexed: 07/23/2024] Open
Abstract
Background Though the artificial neural network (ANN) technique has been used to predict noise-induced hearing loss (NIHL), the established prediction models have primarily relied on cross-sectional datasets, and hence, they may not comprehensively capture the chronic nature of NIHL as a disease linked to long-term noise exposure among workers. Methods A comprehensive dataset was utilized, encompassing eight-year longitudinal personal hearing threshold levels (HTLs) as well as information on seven personal variables and two environmental variables to establish NIHL predicting models through the ANN technique. Three subdatasets were extracted from the afirementioned comprehensive dataset to assess the advantages of the present study in NIHL predictions. Results The dataset was gathered from 170 workers employed in a steel-making industry, with a median cumulative noise exposure and HTL of 88.40 dBA-year and 19.58 dB, respectively. Utilizing the longitudinal dataset demonstrated superior prediction capabilities compared to cross-sectional datasets. Incorporating the more comprehensive dataset led to improved NIHL predictions, particularly when considering variables such as noise pattern and use of personal protective equipment. Despite fluctuations observed in the measured HTLs, the ANN predicting models consistently revealed a discernible trend. Conclusions A consistent correlation was observed between the measured HTLs and the results obtained from the predicting models. However, it is essential to exercise caution when utilizing the model-predicted NIHLs for individual workers due to inherent personal fluctuations in HTLs. Nonetheless, these ANN models can serve as a valuable reference for the industry in effectively managing its hearing conservation program.
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Affiliation(s)
- Thanawat Khajonklin
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Yih-Min Sun
- Department of Occupational Safety and Health, Chung Hwa University of Medical Technology, Tainan County, Taiwan
| | - Yue-Liang Leon Guo
- Department of Environmental and Occupational Medicine, Medical College, National Taiwan University, Taipei City, Taiwan
| | - Hsin-I Hsu
- Environmental and Labor Affairs Division, Southern Taiwan Science Park Bureau, Ministry of Science and Technology, Tainan City, Taiwan
| | - Chung Sik Yoon
- Department of Environmental Health Sciences, Seoul National University Graduate School of Public Health, Seoul, Republic of Korea
| | - Cheng-Yu Lin
- Department of Otolaryngology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Perng-Jy Tsai
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
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Chen MB, Li MH, Wu LY, Wang R, Long X, Zhang L, Sun W, Guo WW, Pan Y, Zhang YS, Lin C, Shi X, Yang SM. Oridonin employs interleukin 1 receptor type 2 to treat noise-induced hearing loss by blocking inner ear inflammation. Biochem Pharmacol 2023; 210:115457. [PMID: 36806583 DOI: 10.1016/j.bcp.2023.115457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/09/2023] [Accepted: 02/10/2023] [Indexed: 02/18/2023]
Abstract
NOD-like receptor protein 3 (NLRP3) inflammasomes trigger the inflammatory cascades and participate in various inflammatory diseases, including noise-induced hearing loss (NIHL) caused by oxidative stress. Recently, the anti-inflammatory traditional medicine oridonin (Ori) has been reported to provide hearing protection in mice after noise exposure by blocking the NLRP3-never in mitosis gene A-related kinase 7 (NEK7)-inflammasome complex assembly. Using RNA sequencing analysis, we further elucidated that interleukin 1 receptor type 2 (IL1R2) may be another crucial factor regulated by Ori to protect NIHL. We observed that IL1R2 expression was localized in spiral ganglion neurons, inner and outer hair cells, in Ori-treated mouse cochleae. Additionally, we confirmed that ectopic overexpression of IL1R2 in the inner ears of healthy mice using an adeno-associated virus delivery system significantly reduced noise-induced ribbon synapse lesions and hearing loss by blocking the "cytokine storm" in the inner ear. This study provides a novel theoretical foundation for guiding the clinical treatment of NIHL.
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Affiliation(s)
- Meng-Bing Chen
- The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian, China; College of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing 100853, China; Ankang People's Hospital, Ankang 725000, Shanxi, China
| | - Meng-Hua Li
- Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Pharmaceutical Sciences, Hainan University, Haikou 570228, Hainan, China; Academician Workstation of Hainan University (School of Pharmaceutical Sciences), Yazhou Bay, Sanya 572000, Hainan, China; Artificial Auditory Laboratory of Jiangsu Province, Xuzhou Medical University, Xuzhou 221000, Jiangsu, China
| | - Li-Yuan Wu
- Artificial Auditory Laboratory of Jiangsu Province, Xuzhou Medical University, Xuzhou 221000, Jiangsu, China; The Second Affiliated Hospital of Jiaxing University, Jiaxing 314000, Zhejiang, China
| | - Rong Wang
- The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian, China; College of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing 100853, China
| | - Xi Long
- Chongqing Academy of Animal Sciences, Chongqing 402460, China
| | - Liang Zhang
- Chongqing Academy of Animal Sciences, Chongqing 402460, China
| | - Wei Sun
- Department of Communicative Disorders and Sciences, Center for Hearing and Deafness, the State University of New York at Buffalo, Buffalo 14200, NY, USA
| | - Wei-Wei Guo
- College of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing 100853, China
| | - Yong Pan
- Xuzhou Infectious Diseases Hospital, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, Jiangsu, China
| | - Yun-Shi Zhang
- Xuzhou Infectious Diseases Hospital, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, Jiangsu, China
| | - Chang Lin
- The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian, China.
| | - Xi Shi
- Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Pharmaceutical Sciences, Hainan University, Haikou 570228, Hainan, China; Academician Workstation of Hainan University (School of Pharmaceutical Sciences), Yazhou Bay, Sanya 572000, Hainan, China; Artificial Auditory Laboratory of Jiangsu Province, Xuzhou Medical University, Xuzhou 221000, Jiangsu, China.
| | - Shi-Ming Yang
- College of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing 100853, China.
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Moroe N, Mabaso P. Quantifying traffic noise pollution levels: a cross-sectional survey in South Africa. Sci Rep 2022; 12:3454. [PMID: 35236867 PMCID: PMC8891330 DOI: 10.1038/s41598-022-07145-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 02/14/2022] [Indexed: 11/18/2022] Open
Abstract
Despite the alarming increase in environmental noise pollution, particularly road traffic noise, in developing countries, there seems to be no awareness regarding the long-term impacts of noise, specifically traffic noise, on the health outcomes of individuals exposed to excessive noise. Additionally, there is a dearth of studies on noise and its effects utilising the pollution modelling technique known as Pollution Standard Index (PSI) to analyse the impact of noise pollution on exposed individuals. The aim of this study was to investigate the noise levels commuters are exposed to and to apply PSI to determine the level of exposure. We conducted a cross-sectional study at two taxi ranks, over 28 days. Eighty-four noise measurements were collected using a sound level meter and a dosimeter at different times of the day and month, peak vs off-peak hours and busy days vs quiet days. Data were collected between April and July 2019. We used the Pollution Standard Index to analyse the data. Noise levels were above the permissible commercial noise levels as they fell within the extremely dangerous noise sensitivity zone as determined by the PSI. Furthermore, the noise levels fell below the WHO maximum permissible level of 90 dB. There was no statistical difference between the means of the open and closed ranks. Dosimeter noise level recordings fell within the satisfactory zone as measurements were below 300 PSI, which is considered unhealthy. There is a need to raise awareness on the dangers and effects of noise pollution in developing countries, as their populations are exposed to road traffic noise.
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Affiliation(s)
- Nomfundo Moroe
- Department of Speech Pathology and Audiology, University of the Witwatersrand, Johannesburg, South Africa.
| | - Paballo Mabaso
- Department of Speech Pathology and Audiology, University of the Witwatersrand, Johannesburg, South Africa
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