Scholarlink

<p>Marine pollution, characterized by a wide range of contaminants, exerts a significant impact on the health of marine organisms. This study aimed to evaluate the effects of pollutants and four biological indices (R ratio, Metal Pollution Index (MPI), Integrated Metal Bioaccumulation Index (IMBI), and Integrated Biomarker Response (IBR)), on the neuromuscular function of <i>Mytilus galloprovincialis</i>, assessed through acetylcholinesterase (AChE) activity. Twenty independent variables were selected to represent potential drivers of AChE activity, with mean AChE activity serving as the dependent variable. Initially, simple linear regression models were applied to examine the relationship between each independent variable and AChE activity, and non-significant predictors were excluded. Subsequently, multiple linear regression analysis using a forward stepwise method was employed to identify the best predictive model of AChE variability. AChE activity exhibited peaks in April 2017 and September 2018, followed by declines during summer 2017 and January 2018. The multiple regression model explained approximately 51% of the variance in AChE activity, highlighting a moderate explanatory power of environmental and biological factors and AChE response. Furthermore, the results revealed complex interactions between environmental parameters (e.g., precipitation, cadmium concentration, and electrical conductivity) and biomarkers (e.g., Catalase, glutathione-S-transferase), with catalase exerting a significant positive effect on AChE activity. These findings emphasize the usefulness of multiple regression analysis for disentangling the individual contributions of environmental and biological factors to AChE variability in marine organisms.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Effect of pollutants, fecal bacteria and abiotic parameters on prediction of neurobiomarker activity in natural population of the bivalves Mytilus galloprovincialis in south Morocco: using multiple regression analysis

  • 期刊论文

  • 发表日期：

    2026年5月30日

查看全文
  • Youssef El Mourabit,
  • Mustapha Agnaou,
  • Driss Azdem,
  • Ibrahim Alsayer,
  • Jamal Mabrouki,
  • Abdellatif Moukrim,
  • Aicha Ait Alla

摘要

Marine pollution, characterized by a wide range of contaminants, exerts a significant impact on the health of marine organisms. This study aimed to evaluate the effects of pollutants and four biological indices (R ratio, Metal Pollution Index (MPI), Integrated Metal Bioaccumulation Index (IMBI), and Integrated Biomarker Response (IBR)), on the neuromuscular function of Mytilus galloprovincialis, assessed through acetylcholinesterase (AChE) activity. Twenty independent variables were selected to represent potential drivers of AChE activity, with mean AChE activity serving as the dependent variable. Initially, simple linear regression models were applied to examine the relationship between each independent variable and AChE activity, and non-significant predictors were excluded. Subsequently, multiple linear regression analysis using a forward stepwise method was employed to identify the best predictive model of AChE variability. AChE activity exhibited peaks in April 2017 and September 2018, followed by declines during summer 2017 and January 2018. The multiple regression model explained approximately 51% of the variance in AChE activity, highlighting a moderate explanatory power of environmental and biological factors and AChE response. Furthermore, the results revealed complex interactions between environmental parameters (e.g., precipitation, cadmium concentration, and electrical conductivity) and biomarkers (e.g., Catalase, glutathione-S-transferase), with catalase exerting a significant positive effect on AChE activity. These findings emphasize the usefulness of multiple regression analysis for disentangling the individual contributions of environmental and biological factors to AChE variability in marine organisms.