Effects of chronic low-level lead (Pb) exposure on cognitive function and hippocampal neuronal ferroptosis: An integrative approach using bioinformatics analysis, machine learning, and experimental validation.

Lead (Pb), a pervasive and ancient toxic heavy metal, continues to pose significant neurological health risks, particularly in regions such as Southeast Asia. While previous research has primarily focused on the adverse effects of acute, high-level lead exposure on neurological systems, studies on the impacts of chronic, low-level exposure are less extensive, especially regarding the precise mechanisms linking ferroptosis - a novel type of neuron cell death - with cognitive impairment. This study aims to explore the potential effects of chronic low-level lead exposure on cognitive function and hippocampal neuronal ferroptosis. This research represents the first comprehensive investigation into the impact of chronic low-level lead exposure on hippocampal neuronal ferroptosis, spanning clinical settings, bioinformatic analyses, and experimental validation. Our findings reveal significant alterations in the expression of genes associated with iron metabolism and Nrf2-dependent ferroptosis following lead exposure, as evidenced by comparing gene expression in the peripheral blood of lead-acid battery workers and workers without lead exposure. Furthermore, our in vitro and in vivo experimental results strongly suggest that lead exposure may precipitate cognitive dysfunction and induce hippocampal neuronal ferroptosis. In conclusion, our study indicates that chronic low-level lead exposure may activate microglia, leading to the promotion of ferroptosis in hippocampal neurons.

Analysis of the role of PANoptosis in seizures via integrated bioinformatics analysis and experimental validation.

Background: Epilepsy is recognized as the most common chronic neurological condition among children, and hippocampal neuronal cell death has been identified as a crucial factor in the pathophysiological processes underlying seizures. In recent studies, PANoptosis, a newly characterized form of cell death, has emerged as a significant contributor to the development of various neurological disorders, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. PANoptosis involves the simultaneous activation of pyroptosis, apoptosis, and necroptosis within the same population of cells. However, its specific role in the context of seizures remains to be fully elucidated. Further investigation is required to uncover the precise involvement of PANoptosis in the pathogenesis of seizures and to better understand its potential implications for the development of targeted therapeutic approaches in epilepsy. Methods: In this study, the gene expression data of the hippocampus following the administration of kainic acid (KA) or NaCl was obtained from the Gene Expression Omnibus (GEO) database. The PANoptosis-related gene set was compiled from the GeneCards database and previous literature. Time series analysis was performed to analyze the temporal expression patterns of the PANoptosis-related genes. Gene set variation analysis (GSVA), Gene ontology (GO), and Kyoto encyclopedia of genes and genomes (KEGG) were employed to explore potential biological mechanisms underlying PANoptosis and its role in seizures. Weighted gene co-expression network analysis (WGCNA) and differential expression analysis were utilized to identify pivotal gene modules and PANoptosis-related genes associated with the pathophysiological processes underlying seizures. To validate the expression of PANoptosis-related genes, Western blotting or quantitative real-time polymerase chain reaction (qRT-PCR) assays were conducted. These experimental validations were performed in human blood samples, animal models, and cell models to verify the expression patterns of the PANoptosis-related genes and their relevance to epilepsy. Results: The GSVA analysis performed in this study demonstrated that PANoptosis-related genes have the potential to distinguish between the control group and KA-induced epileptic mice. This suggests that the expression patterns of these genes are significantly altered in response to KA-induced epilepsy. Furthermore, the Weighted gene co-expression network analysis (WGCNA) identified the blue module as being highly associated with epileptic phenotypes. This module consists of genes that exhibit correlated expression patterns specifically related to epilepsy. Within the blue module, 10 genes were further identified as biomarker genes for epilepsy. These genes include MLKL, IRF1, RIPK1, GSDMD, CASP1, CASP8, ZBP1, CASP6, PYCARD, and IL18. These genes likely play critical roles in the pathophysiology of epilepsy and could serve as potential biomarkers for diagnosing or monitoring the condition. Conclusion: In conclusion, our study suggests that the hippocampal neuronal cell death in epilepsy may be closely related to PANoptosis, a novel form of cell death, which provides insights into the underlying pathophysiological processes of epilepsy and helps the development of novel therapeutic approaches for epilepsy.

Nondestructive Identification of Rare Trophoblastic Cells by Endoplasmic Reticulum Staining for Noninvasive Prenatal Testing of Monogenic Diseases.

Noninvasive prenatal detection of monogenic diseases based on cell-free DNA is hampered by challenges in obtaining a sufficient fraction and adequate quality of fetal DNA. Analyzing rare trophoblastic cells from Papanicolaou smears carrying the entire fetal genome provides an alternative method for noninvasive detection of monogenic diseases. However, intracellular labeling for identification of target cells can affect the quality of DNA in varying degrees. Here, a new approach is developed for nondestructive identification of rare fetal cells from abundant maternal cells based on endoplasmic reticulum staining and linear discriminant analysis (ER-LDA). Compared with traditional methods, ER-LDA has little effect on cell quality, allowing trophoblastic cells to be analyzed on the single-cell level. Using ER-LDA, high-purity of trophoblastic cells can be identified and isolated at single cell resolution from 60 pregnancies between 4 and 38 weeks of gestation. Pathogenic variants, including -SEA/ deletion mutation and point mutations, in 11 fetuses at risk for α- or ß-thalassemia can be accurately detected by this test. The detection platform can also be extended to analyze the mutational profiles of other monogenic diseases. This simple, low-cost, and noninvasive test can provide valuable fetal cells for fetal genotyping and holds promise for prenatal detection of monogenic diseases.