RESUMO
Exposure assessment is a crucial component of environmental health research, providing essential information on the potential risks associated with various chemicals. A systematic scoping review was conducted to acquire an overview of accessible human exposure assessment methods and computational tools to support and ultimately improve risk assessment. The systematic scoping review was performed in Sysrev, a web platform that introduces machine learning techniques into the review process aiming for increased accuracy and efficiency. Included publications were restricted to a publication date after the year 2000, where exposure methods were properly described. Exposure assessments methods were found to be used for a broad range of environmental chemicals including pesticides, metals, persistent chemicals, volatile organic compounds, and other chemical classes. Our results show that after the year 2000, for all the types of exposure routes, probabilistic analysis, and computational methods to calculate human exposure have increased. Sixty-three mathematical models and toolboxes were identified that have been developed in Europe, North America, and globally. However, only twelve occur frequently and their usefulness were associated with exposure route, chemical classes and input parameters used to estimate exposure. The outcome of the combined associations can function as a basis and/or guide for decision making for the selection of most appropriate method and tool to be used for environmental chemical human exposure assessments in Ontology-driven and artificial intelligence-based repeated dose toxicity testing of chemicals for next generation risk assessment (ONTOX) project and elsewhere. Finally, the choice of input parameters used in each mathematical model and toolbox shown by our analysis can contribute to the harmonization process of the exposure models and tools increasing the prospect for comparison between studies and consistency in the regulatory process in the future.
Assuntos
Exposição Ambiental , Poluentes Ambientais , Humanos , Exposição Ambiental/estatística & dados numéricos , Monitoramento Ambiental/métodos , Aprendizado de Máquina , Praguicidas/toxicidade , Medição de Risco/métodosRESUMO
The field of chemical toxicity testing is undergoing a transition to overcome the limitations of in vivo experiments. This evolution involves implementing innovative non-animal approaches to improve predictability and provide a more precise understanding of toxicity mechanisms. Adverse outcome pathway (AOP) networks are pivotal in organizing existing mechanistic knowledge related to toxicological processes. However, these AOP networks are dynamic and require regular updates to incorporate the latest data. Regulatory challenges also persist due to concerns about the reliability of the information they offer. This study introduces a generic Weight-of-Evidence (WoE) scoring method, aligned with the tailored Bradford-Hill criteria, to quantitatively assess the confidence levels in key event relationships (KERs) within AOP networks. We use the previously published AOP network on chemical-induced liver steatosis, a prevalent form of human liver injury, as a case study. Initially, the existing AOP network is optimized with the latest scientific information extracted from PubMed using the free SysRev platform for artificial intelligence (AI)-based abstract inclusion and standardized data collection. The resulting optimized AOP network, constructed using Cytoscape, visually represents confidence levels through node size (key event, KE) and edge thickness (KERs). Additionally, a Shiny application is developed to facilitate user interaction with the dataset, promoting future updates. Our analysis of 173 research papers yielded 100 unique KEs and 221 KERs among which 72 KEs and 170 KERs, respectively, have not been previously documented in the prior AOP network or AOP-wiki. Notably, modifications in de novo lipogenesis, fatty acid uptake and mitochondrial beta-oxidation, leading to lipid accumulation and liver steatosis, garnered the highest KER confidence scores. In conclusion, our study delivers a generic methodology for developing and assessing AOP networks. The quantitative WoE scoring method facilitates in determining the level of support for KERs within the optimized AOP network, offering valuable insights into its utility in both scientific research and regulatory contexts. KERs supported by robust evidence represent promising candidates for inclusion in an in vitro test battery for reliably predicting chemical-induced liver steatosis within regulatory frameworks.
Assuntos
Rotas de Resultados Adversos , Fígado Gorduroso , Humanos , Fígado Gorduroso/induzido quimicamente , Animais , Doença Hepática Induzida por Substâncias e Drogas/etiologia , Testes de Toxicidade/métodos , Inteligência ArtificialRESUMO
Huntington's disease is characterized by the formation of protein aggregates, which can be degraded by macroautophagy. Here, we studied protein levels and intracellular distribution of p62 and NBR1, two macroautophagy cargo receptors, during disease progression. In R6/1 mice, p62 and NBR1 protein levels were decreased in all brain regions analyzed early in the disease, whereas at late stages they accumulated in the striatum and hippocampus, but not in the cortex. The accumulation of p62, but not NBR1, occurred in neuronal nuclei, where it co-localized with mutant huntingtin inclusions, both in R6/1 and Huntington's disease patients. Moreover, exportin-1 was selectively decreased in old R6/1 mice brain, and could worsen p62 nuclear accumulation. In conclusion, p62 interacts with mutant huntingtin and is retained in the nucleus along the progression of the disease, mostly in striatal and hippocampal neurons. Thus, cytoplasmic NBR1 might be important to maintain basal levels of selective macroautophagy in these neurons.
Assuntos
Córtex Cerebral/metabolismo , Corpo Estriado/metabolismo , Hipocampo/metabolismo , Doença de Huntington/metabolismo , Proteínas/metabolismo , Fatores de Transcrição/metabolismo , Fatores Etários , Animais , Núcleo Celular/metabolismo , Citoplasma/metabolismo , Modelos Animais de Doenças , Progressão da Doença , Humanos , Proteína Huntingtina , Corpos de Inclusão/metabolismo , Peptídeos e Proteínas de Sinalização Intracelular , Carioferinas/metabolismo , Masculino , Camundongos , Camundongos Transgênicos , Proteínas do Tecido Nervoso/metabolismo , Neurônios/metabolismo , Proteínas Nucleares/metabolismo , Especificidade de Órgãos , Receptores Citoplasmáticos e Nucleares/metabolismo , Fator de Transcrição TFIIH , Proteína Exportina 1RESUMO
Faithful chromosome segregation during mitosis relies on a proofreading mechanism that monitors proper kinetochore-microtubule attachments. The spindle assembly checkpoint (SAC) is based on the concerted action of numerous components that maintain a repressive signal inhibiting transition into anaphase until all chromosomes are attached. Here we show that A-Kinase Anchoring Protein 95 (AKAP95) is necessary for proper SAC function. AKAP95-depleted HeLa cells show micronuclei formed from lagging chromosomes at mitosis. Using a BioID proximity-based proteomic screen, we identify the nuclear pore complex protein TPR as a novel AKAP95 binding partner. We show interaction between AKAP95 and TPR in mitosis, and an AKAP95-dependent enrichment of TPR in the spindle microtubule area in metaphase, then later in the spindle midzone area. AKAP95-depleted cells display faster prometaphase to anaphase transition, escape from nocodazole-induced mitotic arrest and show a partial delocalization from kinetochores of the SAC component MAD1. Our results demonstrate an involvement of AKAP95 in proper SAC function likely through its interaction with TPR.
Assuntos
Proteínas de Ancoragem à Quinase A/genética , Pontos de Checagem da Fase M do Ciclo Celular/genética , Complexo de Proteínas Formadoras de Poros Nucleares/genética , Proteômica , Proteínas Proto-Oncogênicas/genética , Segregação de Cromossomos/genética , Células HeLa , Humanos , Mitose/genética , Poro Nuclear/genética , Poro Nuclear/metabolismo , Complexo de Proteínas Formadoras de Poros Nucleares/metabolismo , Ligação Proteica , Fuso Acromático/genética , Fuso Acromático/metabolismoRESUMO
A balance between cell survival and apoptosis is crucial to avoid neurodegeneration. Here, we analyzed whether the pro-apoptotic protein PKCδ, and the pro-survival PKCα and ßII, were dysregulated in the brain of R6/1 mouse model of Huntington's disease (HD). Protein levels of the three PKCs examined were reduced in all the brain regions analyzed being PKCδ the most affected isoform. Interestingly, PKCδ protein levels were also decreased in the striatum and cortex of R6/2 and Hdh(Q111/Q111) mice, and in the putamen of HD patients. Nuclear PKCδ induces apoptosis, but we detected reduced PKCδ in both cytoplasmic and nuclear enriched fractions from R6/1 mouse striatum, cortex and hippocampus. In addition, we show that phosphorylation and ubiquitination of PKCδ are increased in 30-week-old R6/1 mouse brain. All together these results suggest a pro-survival role of reduced PKCδ levels in response to mutant huntingtin-induced toxicity. In fact, we show that over-expression of PKCδ increases mutant huntingtin-induced cell death in vitro, whereas over-expression of a PKCδ dominant negative form or silencing of endogenous PKCδ partially blocks mutant huntingtin-induced cell death. Finally, we show that the analysis of lamin B protein levels could be a good marker of PKCδ activity, but it is not involved in PKCδ-mediated cell death in mutant huntingtin-expressing cells. In conclusion, our results suggest that neurons increase the degradation of PKCδ as a compensatory pro-survival mechanism in response to mutant huntingtin-induced toxicity that can help to understand why cell death appears late in the disease.