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Diquat (DQ) is a nonselective bipyridine herbicide with a structure resembling paraquat (PQ). In recent years, the utilization of DQ as a substitute for PQ has grown, leading to an increase in DQ poisoning cases. While the toxicity mechanism of DQ remains unclear, it is primarily attributed to the intracellular generation of reactive oxygen species (ROS) and reactive nitrogen species (RNS) through the process of reduction oxidation. This results in oxidative stress, leading to a cascade of clinical symptoms. Notably, recent reports on DQ poisoning have highlighted a concerning trend: an upsurge in cases involving neurological damage caused by DQ poisoning. These patients often present with severe illness and a high mortality rate, with no effective treatment available thus far. Imaging findings from these cases have shown that neurological damage tends to concentrate on the brainstem. However, the specific mechanisms behind this poisoning remain unclear, and no specific antidote exists. This review summarizes the research progress on DQ poisoning and explores potential mechanisms. By shedding light on the nerve damage associated with DQ poisoning, we hope to raise awareness, propose new avenues for investigating the mechanisms of DQ poisoning, and lay the groundwork for the development of treatment strategies for DQ poisoning. Trial registration number: 2024PS174K. [ABSTRACT FROM AUTHOR]

Fischer plots are widely used in paleoenvironmental research as graphic representations of sea- and lake-level changes through mapping linearly corrected variation of accumulative cycle thickness over cycle number or stratum depth. Some kinds of paleoenvironmental proxy data (especially subsurface data, such as natural gamma-ray logging data), which preserve continuous cyclic signals and have been largely collected, are potential materials for constructing Fischer Plots. However, it is laborious to count the cycles preserved in these proxy data manually and map Fischer plots with these cycles. In this paper, we introduce an original open-source Python code "PyFISCHERPLOT" for constructing Fischer Plots in batches utilizing paleoenvironmental proxy data series. The principle of constructing Fischer plots based on proxy data, the data processing and usage of the PyFISCHERPLOT code and the application cases of the code are presented. The code is compared with existing methods for constructing Fischer plots. [ABSTRACT FROM AUTHOR]