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1.
Chem Res Toxicol ; 35(12): 2219-2226, 2022 12 19.
Artigo em Inglês | MEDLINE | ID: mdl-36475638

RESUMO

The development of toxicity classification models using the ToxCast database has been extensively studied. Machine learning approaches are effective in identifying the bioactivity of untested chemicals. However, ToxCast assays differ in the amount of data and degree of class imbalance (CI). Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. In this study, the effects of CI and data scarcity (DS) on the performance of binary classification models were investigated using ToxCast bioassay data. An assay matrix based on CI and DS was prepared for 335 assays with biologically intended target information, and 28 CI assays and 3 DS assays were selected. Thirty models established by combining five molecular fingerprints (i.e., Morgan, MACCS, RDKit, Pattern, and Layered) and six algorithms [i.e., gradient boosting tree, random forest (RF), multi-layered perceptron, k-nearest neighbor, logistic regression, and naive Bayes] were trained using the selected assay data set. Of the 30 trained models, MACCS-RF showed the best performance and thus was selected for analyses of the effects of CI and DS. Results showed that recall and F1 were significantly lower when training with the CI assays than with the DS assays. In addition, hyperparameter tuning of the RF algorithm significantly improved F1 on CI assays. This study provided a basis for developing a toxicity classification model with improved performance by evaluating the effects of data set characteristics. This study also emphasized the importance of using appropriate evaluation metrics and tuning hyperparameters in model development.


Assuntos
Modelos Logísticos , Aprendizado de Máquina , Toxicologia , Algoritmos , Teorema de Bayes , Bioensaio , Toxicologia/métodos , Testes de Toxicidade
5.
Toxicol Pathol ; 50(7): 836-857, 2022 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-36165586

RESUMO

The 2022 annual National Toxicology Program Satellite Symposium, entitled "Pathology Potpourri," was held in Austin, Texas at the Society of Toxicologic Pathology's 40th annual meeting during a half-day session on Sunday, June 19. The goal of this symposium was to present and discuss challenging diagnostic pathology and/or nomenclature issues. This article presents summaries of the speakers' talks along with select images that were used by the audience for voting and discussion. Various lesions and topics covered during the symposium included induced and spontaneous neoplastic and nonneoplastic lesions in the mouse lung, spontaneous lesions in the reproductive tract of a female cynomolgus macaque, induced vascular lesions in a mouse asthma model and interesting case studies in a rhesus macaque, dog and genetically engineered mouse model.


Assuntos
Toxicologia , Camundongos , Feminino , Animais , Cães , Macaca mulatta , Macaca fascicularis
7.
J Med Toxicol ; 18(4): 267-296, 2022 10.
Artigo em Inglês | MEDLINE | ID: mdl-36070069

RESUMO

The Toxicology Investigators Consortium (ToxIC) Core Registry was established by the American College of Medical Toxicology in 2010. The Core Registry collects data from participating sites with the agreement that all bedside and telehealth medical toxicology consultations will be entered. This twelfth annual report summarizes the registry's 2021 data and activity with its additional 8552 cases. Cases were identified for inclusion in this report by a query of the ToxIC database for any case entered from January 1 to December 31, 2021. Detailed data was collected from these cases and aggregated to provide information, which included demographics, reason for medical toxicology evaluation, agent and agent class, clinical signs and symptoms, treatments and antidotes administered, mortality, and whether life support was withdrawn. Gender distribution included 50.4% of cases in females, 48.2% of cases in males, and 1.4% of cases in transgender or gender non-conforming individuals. Non-opioid analgesics were the most commonly reported agent class (14.9%), followed by opioids (13.1%). Acetaminophen was the most common agent reported. Fentanyl was the most common opioid reported and was responsible for the greatest number of fatalities. There were 120 fatalities, comprising 1.4% of all cases. Major trends in demographics and exposure characteristics remained similar to past years' reports. Sub-analyses were conducted to describe new demographic characteristics, including marital status, housing status and military service, the continued COVID-19 pandemic and related toxicologic exposures, and novel substances of exposure.


Assuntos
Analgésicos não Narcóticos , COVID-19 , Overdose de Drogas , Toxicologia , Acetaminofen , Analgésicos Opioides , Antídotos , Overdose de Drogas/diagnóstico , Overdose de Drogas/epidemiologia , Overdose de Drogas/terapia , Feminino , Fentanila , Humanos , Masculino , Pandemias , Sistema de Registros , Estados Unidos/epidemiologia
8.
Vet Clin Pathol ; 51(3): 311-329, 2022 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-35975895

RESUMO

Integrating clinical pathology data with anatomic pathology data is a common practice when reporting findings in the context of nonclinical toxicity studies and aids in understanding and communicating the nonclinical safety profile of test articles in development. Appropriate pathology data integration requires knowledge of analyte and tissue biology, species differences, methods of specimen acquisition and analysis, study procedures, and an understanding of the potential causes and effects of a variety of pathophysiologic processes. Neglecting these factors can lead to inappropriate data integration or a missed opportunity to enhance understanding and communication of observed changes. In such cases, nonclinical safety information relevant to human safety risk assessment may be misrepresented or misunderstood. This "Points to Consider" manuscript presents general concepts regarding pathology data integration in nonclinical studies, considerations for avoiding potential oversights and errors in data integration, and focused discussion on topics relevant to data integration for several key organ systems, including liver, kidney, and cardiovascular systems.


Assuntos
Patologia Clínica , Toxicologia , Animais , Avaliação Pré-Clínica de Medicamentos/métodos , Avaliação Pré-Clínica de Medicamentos/veterinária , Humanos , Patologia Clínica/métodos , Políticas
9.
Int J Mol Sci ; 23(16)2022 Aug 16.
Artigo em Inglês | MEDLINE | ID: mdl-36012476

RESUMO

The Special Issue "Toxicology, Nanotoxicology and Occupational Diseases" of the International Journal of Molecular Sciences includes six articles presenting the results of recent experimental studies in the fields of toxicology, nanotoxicology, and occupational health [...].


Assuntos
Nanoestruturas , Doenças Profissionais , Exposição Ocupacional , Toxicologia , Humanos , Nanoestruturas/química , Doenças Profissionais/induzido quimicamente , Exposição Ocupacional/efeitos adversos , Toxicologia/métodos
10.
Chem Res Toxicol ; 35(7): 1127-1128, 2022 07 18.
Artigo em Inglês | MEDLINE | ID: mdl-35844151
11.
Environ Sci Technol ; 56(16): 11132-11145, 2022 08 16.
Artigo em Inglês | MEDLINE | ID: mdl-35881918

RESUMO

The toxicity evaluation system of environmental pollutants has undergone numerous changes due to the application of new technologies. Single-cell toxicogenomics is rapidly changing our view on environmental toxicology by increasing the resolution of our analysis to the level of a single cell. Applications of this technology in environmental toxicology have begun to emerge and are rapidly expanding the portfolio of existing technologies and applications. Here, we first summarized different methods involved in single-cell isolation and amplification in single-cell sequencing process, compared the advantages and disadvantages of different methods, and analyzed their development trends. Then, we reviewed the main advances of single-cell toxicogenomics in environmental toxicology, emphatically analyzed the application prospects of this technology in identifying the target cells of pollutants in early embryos, clarifying the heterogeneous response of cell subtypes to pollutants, and finding pathogenic bacteria in unknown microbes, and highlighted the unique characteristics of this approach with high resolution, high throughput, and high specificity by examples. We also offered a prediction of the further application of this technology and the revolution it brings in environmental toxicology. Overall, these advances will provide practical solutions for controlling or mitigating exogenous toxicological effects that threaten human and ecosystem health, contribute to improving our understanding of the physiological processes affected by pollutants, and lead to the emergence of new methods of pollution control.


Assuntos
Poluentes Ambientais , Toxicologia , Ecossistema , Ecotoxicologia , Poluentes Ambientais/toxicidade , Humanos , Toxicogenética , Toxicologia/métodos
12.
Toxicol Pathol ; 50(6): 808-826, 2022 08.
Artigo em Inglês | MEDLINE | ID: mdl-35852467

RESUMO

Integrating clinical pathology data with anatomic pathology data is a common practice when reporting findings in the context of nonclinical toxicity studies and aids in understanding and communicating the nonclinical safety profile of test articles in development. Appropriate pathology data integration requires knowledge of analyte and tissue biology, species differences, methods of specimen acquisition and analysis, study procedures, and an understanding of the potential causes and effects of a variety of pathophysiologic processes. Neglecting these factors can lead to inappropriate data integration or a missed opportunity to enhance understanding and communication of observed changes. In such cases, nonclinical safety information relevant to human safety risk assessment may be misrepresented or misunderstood. This "Points to Consider" manuscript presents general concepts regarding pathology data integration in nonclinical studies, considerations for avoiding potential oversights and errors in data integration, and focused discussion on topics relevant to data integration for several key organ systems including liver, kidney, and cardiovascular system.


Assuntos
Patologia Clínica , Toxicologia , Humanos , Patologia Clínica/métodos , Políticas , Medição de Risco , Toxicologia/métodos
13.
Int J Mol Sci ; 23(13)2022 Jun 29.
Artigo em Inglês | MEDLINE | ID: mdl-35806235

RESUMO

Toxicology is an incredibly complex and diverse area of biomedical science that includes numerous areas of specialization [...].


Assuntos
Substâncias Perigosas , Toxicologia
14.
Chem Res Toxicol ; 35(8): 1370-1382, 2022 08 15.
Artigo em Inglês | MEDLINE | ID: mdl-35819939

RESUMO

ComptoxAI is a new data infrastructure for computational and artificial intelligence research in predictive toxicology. Here, we describe and showcase ComptoxAI's graph-structured knowledge base in the context of three real-world use-cases, demonstrating that it can rapidly answer complex questions about toxicology that are infeasible using previous technologies and data resources. These use-cases each demonstrate a tool for information retrieval from the knowledge base being used to solve a specific task: The "shortest path" module is used to identify mechanistic links between perfluorooctanoic acid (PFOA) exposure and nonalcoholic fatty liver disease; the "expand network" module identifies communities that are linked to dioxin toxicity; and the quantitative structure-activity relationship (QSAR) dataset generator predicts pregnane X receptor agonism in a set of 4,021 pesticide ingredients. The contents of ComptoxAI's source data are rigorously aggregated from a diverse array of public third-party databases, and ComptoxAI is designed as a free, public, and open-source toolkit to enable diverse classes of users including biomedical researchers, public health and regulatory officials, and the general public to predict toxicology of unknowns and modes of action.


Assuntos
Biologia Computacional , Toxicologia , Inteligência Artificial , Bases de Dados Factuais , Relação Quantitativa Estrutura-Atividade
15.
Environ Sci Technol ; 56(16): 11100-11102, 2022 08 16.
Artigo em Inglês | MEDLINE | ID: mdl-35895873
16.
Rev. toxicol ; 39(2): 1, jul.-dic. 2022.
Artigo em Espanhol | IBECS | ID: ibc-213629
17.
Toxicol Pathol ; 50(4): 531-543, 2022 06.
Artigo em Inglês | MEDLINE | ID: mdl-35657014

RESUMO

The Society of Toxicologic Pathology's Scientific and Regulatory Policy Committee formed a working group to consider the present and future use of digital pathology in toxicologic pathology in general and specifically its use in primary evaluation and peer review in Good Laboratory Practice (GLP) environments. Digital histopathology systems can save costs by reducing travel, enhancing organizational flexibility, decreasing slide handling, improving collaboration, increasing access to historical images, and improving quality and efficiency through integration with laboratory information management systems. However, the resources to implement and operate a digital pathology system can be significant. Given the magnitude and risks involved in the decision to adopt digital histopathology, this working group used pertinent previously published survey results and its members' expertise to create a Points-to-Consider article to assist organizations with building and implementing digital pathology workflows. With the aim of providing a comprehensive perspective, the current publication summarizes aspects of digital whole-slide imaging relevant to nonclinical histopathology evaluations, and then presents points to consider applicable to both primary digital histopathology evaluation and digital peer review in GLP toxicology studies. The Supplemental Appendices provide additional tabulated resources.


Assuntos
Revisão por Pares , Toxicologia , Laboratórios , Políticas , Projetos de Pesquisa , Toxicologia/métodos
18.
Sud Med Ekspert ; 65(3): 45-48, 2022.
Artigo em Russo | MEDLINE | ID: mdl-35613448

RESUMO

Today, one of the most effective tools for high-quality training of specialists at the postgraduate level is continuous professional development (CPD). Additional professional education of specialists in the field of forensic chemical and chemical-toxicological analysis with higher non-medical education (pharmaceutical, chemical, biological) is carried out on the basis of pharmaceutical and medical higher educational institutions, autonomous non-profit organizations through the implementation of additional professional training programs. The timing, forms, content and technology of training by organizations implementing the corresponding educational program are of great importance. Analysis of the results of the questionnaire survey of expert chemists, carried out according to the original questionnaire in 2020-2021 in some regions of Russia, showed the main directions of development of the training system, forms and methods of teaching, the need to develop appropriate software.


Assuntos
Medicina Legal , Competência Profissional , Toxicologia , Medicina Legal/educação , Humanos , Federação Russa , Inquéritos e Questionários , Toxicologia/educação
19.
Emerg Med Clin North Am ; 40(2): 431-441, 2022 May.
Artigo em Inglês | MEDLINE | ID: mdl-35461632

RESUMO

When evaluating a potentially poisoned patient, there is no substitute for a thorough history and physical examination. Clues from the examination are generally more likely to be helpful than a "shotgun" laboratory approach that involves indiscriminate testing of blood or urine for multiple agents. When used appropriately, diagnostic tests may be of help in the management of the intoxicated patient. When a specific toxin or even class of toxins is suspected, requesting qualitative or quantitative levels may be appropriate. The purpose of this review is to examine the role of common diagnostic tests in the evaluation of the poisoned patient.


Assuntos
Intoxicação , Venenos , Toxicologia , Humanos , Intoxicação/diagnóstico , Intoxicação/terapia
20.
Emerg Med Clin North Am ; 40(2): xiii-xiv, 2022 05.
Artigo em Inglês | MEDLINE | ID: mdl-35461633
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