Emerging Toxicity Models from Emerging Scientists.
Ontology highlight
ABSTRACT:
SUBMITTER: Allard P
PROVIDER: S-EPMC4433035 | biostudies-literature | 2015 May
REPOSITORIES: biostudies-literature
Publications
Toxicology has seen a recent influx of new talents from other fields attracted by the application of their expertise to pressing questions of toxicological and environmental relevance. This transition has opened the door to innovative and exciting scientific opportunities but has also generated a new set of questions and challenges. In this viewpoint article, I will highlight some of the drivers and hurdles encountered by the recent new breeds of toxicologists. ...[more]
Similar Datasets
Project description:BackgroundThe new REACH legislation requires assessment of a large number of chemicals in the European market for several endpoints. Developmental toxicity is one of the most difficult endpoints to assess, on account of the complexity, length and costs of experiments. Following the encouragement of QSAR (in silico) methods provided in the REACH itself, the CAESAR project has developed several models.ResultsTwo QSAR models for developmental toxicity have been developed, using different statistical/mathematical methods. Both models performed well. The first makes a classification based on a random forest algorithm, while the second is based on an adaptive fuzzy partition algorithm. The first model has been implemented and inserted into the CAESAR on-line application, which is java-based software that allows everyone to freely use the models.ConclusionsThe CAESAR QSAR models have been developed with the aim to minimize false negatives in order to make them more usable for REACH. The CAESAR on-line application ensures that both industry and regulators can easily access and use the developmental toxicity model (as well as the models for the other four endpoints).
| S-EPMC2913331 | biostudies-literature
Project description:Background and purposeAmyloid-? (A?) aggregation into synaptotoxic, prefibrillar oligomers is a major pathogenic event underlying the neuropathology of Alzheimer's disease (AD). The pharmacological and neuroprotective properties of a novel A? aggregation inhibitor, SEN1269, were investigated on aggregation and cell viability and in test systems relevant to synaptic function and memory, using both synthetic A?(1-42) and cell-derived A? oligomers.Experimental approachSurface plasmon resonance studies measured binding of SEN1269 to A?(1-42) . Thioflavin-T fluorescence and MTT assays were used to measure its ability to block A?(1-42) -induced aggregation and reduction in cell viability. In vitro and in vivo long-term potentiation (LTP) experiments measured the effect of SEN1269 on deficits induced by synthetic A?(1-42) and cell-derived A? oligomers. Following i.c.v. administration of the latter, a complex (alternating-lever cyclic ratio) schedule of operant responding measured effects on memory in freely moving rats.Key resultsSEN1269 demonstrated direct binding to monomeric A?(1-42) , produced a concentration-related blockade of A?(1-42) aggregation and protected neuronal cell lines exposed to A?(1-42) . In vitro, SEN1269 alleviated deficits in hippocampal LTP induced by A?(1-42) and cell-derived A? oligomers. In vivo, SEN1269 reduced the deficits in LTP and memory induced by i.c.v. administration of cell-derived A? oligomers.Conclusions and implicationsSEN1269 protected cells exposed to A?(1-42) , displayed central activity with respect to reducing A?-induced neurotoxicity and was neuroprotective in electrophysiological and behavioural models of memory relevant to A?-induced neurodegeneration. It represents a promising lead for designing inhibitors of A?-mediated synaptic toxicity as potential neuroprotective agents for treating AD.
| S-EPMC3481045 | biostudies-literature
Project description:Immunotherapy has emerged as one of the most promising approaches for ovarian cancer treatment. The tumor microenvironment (TME) is a key factor to consider when stimulating antitumoral responses as it consists largely of tumor promoting immunosuppressive cell types that attenuate antitumor immunity. As our understanding of the determinants of the TME composition grows, we have begun to appreciate the need to address both inter- and intra-tumor heterogeneity, mutation/neoantigen burden, immune landscape, and stromal cell contributions. The majority of immunotherapy studies in ovarian cancer have been performed using the well-characterized murine ID8 ovarian carcinoma model. Numerous other animal models of ovarian cancer exist, but have been underutilized because of their narrow initial characterizations in this context. Here, we describe animal models that may be untapped resources for the immunotherapy field because of their shared genomic alterations and histopathology with human ovarian cancer. We also shed light on the strengths and limitations of these models, and the knowledge gaps that need to be addressed to enhance the utility of preclinical models for testing novel immunotherapeutic approaches.
| S-EPMC6115831 | biostudies-literature
Project description:Respiratory tissues are bombarded by billions of particles daily. If allowed to accumulate, these particles can cause injury, inflammation, or infection, and thus may significantly disrupt airflow and gas exchange. Mucociliary defense, a primary mechanism for protecting host tissues, operates through the coordinated functions of mucus and cilia that trap and eliminate inhaled materials. Mucociliary function is also required for the elimination of endogenous cells and debris. Although defense is necessarily robust, it is also tightly regulated to minimize physiologic disruption of the host. Indeed, mucociliary dysfunction contributes to the pathogenesis of many lung diseases-including asthma, chronic obstructive pulmonary disease, pulmonary fibrosis, and cystic fibrosis-in which airflow limitation, inflammation, persistent tissue injury, and structural remodeling occur. Here, we highlight recent advances in cilia and mucin biology, the importance of well-controlled mucociliary interactions, and the need to better understand how these regulate innate barrier and immune defense.
| S-EPMC6322027 | biostudies-literature
Project description:Cancer heterogeneity is regarded as the main reason for the failure of conventional cancer therapy. The ability to reconstruct intra- and interpatient heterogeneity in cancer models is crucial for understanding cancer biology as well as for developing personalized anti-cancer therapy. Cancer organoids represent an emerging approach for creating patient-derived in vitro cancer models that closely recapitulate the pathophysiological features of natural tumorigenesis and metastasis. Meanwhile, cancer organoids have recently been utilized in the discovery of personalized anti-cancer therapy and prognostic biomarkers. Further, the synergistic combination of cancer organoids with organ-on-a-chip and 3D bioprinting presents a new avenue in the development of more sophisticated and optimized model systems to recapitulate complex cancer-stroma or multiorgan metastasis. Here, we summarize the recent advances in cancer organoids from a perspective of the in vitro emulation of natural cancer evolution and the applications in personalized cancer theranostics. We also discuss the challenges and trends in reconstructing more comprehensive cancer models for basic and clinical cancer research.
| S-EPMC6936115 | biostudies-literature
Project description:Genomic imprinting is an epigenetically-regulated process of central importance in mammalian development and evolution. It involves multiple levels of regulation, with spatio-temporal heterogeneity, leading to the context-dependent and parent-of-origin specific expression of a small fraction of the genome. Genomic imprinting studies have therefore been essential to increase basic knowledge in functional genomics, evolution biology and developmental biology, as well as with regard to potential clinical and agrigenomic perspectives. Here we offer an overview on the contribution of livestock research, which features attractive resources in several respects, for better understanding genomic imprinting and its functional impacts. Given the related broad implications and complexity, we promote the use of such resources for studying genomic imprinting in a holistic and integrative view. We hope this mini-review will draw attention to the relevance of livestock genomic imprinting studies and stimulate research in this area.
| S-EPMC10945557 | biostudies-literature
Project description:Assessing the non-lethal effects of disturbance from human activities is necessary for wildlife conservation and management. However, linking short-term responses to long-term impacts on individuals and populations is a significant hurdle for evaluating the risks of a proposed activity. The Population Consequences of Disturbance (PCoD) framework conceptually describes how disturbance can lead to changes in population dynamics, and its real-world application has led to a suite of quantitative models that can inform risk assessments. Here, we review PCoD models that forecast the possible consequences of a range of disturbance scenarios for marine mammals. In so doing, we identify common themes and highlight general principles to consider when assessing risk. We find that, when considered holistically, these models provide valuable insights into which contextual factors influence a population's degree of exposure and sensitivity to disturbance. We also discuss model assumptions and limitations, identify data gaps and suggest future research directions to enable PCoD models to better inform risk assessments and conservation and management decisions. The general principles explored can help wildlife managers and practitioners identify and prioritize the populations most vulnerable to disturbance and guide industry in planning activities that avoid or mitigate population-level effects.
| S-EPMC8385386 | biostudies-literature
Project description:OBJECTIVES:To explore the factors that influence career progress for early stage clinician-scientists and to identify ways to mitigate these factors in the context of emerging Asian academic medical centres (AMCs). DESIGN:Qualitative interviews and thematic data analysis based on grounded theory. SETTING AND PARTICIPANTS:Five focus group interviews comprising 29 early career clinician-scientists who have received their first national-level career development award in Singapore. RESULTS:Clinical priorities represented an overarching concern with many reporting the difficulty in delineating responsibilities between clinical care and research. Additionally, there was a prevailing perception of the lack of support for research at the institutional level. Participants tended to identify mentors through their own efforts in a relatively haphazard manner, often owing to the dearth of role models and perceived inadequacy of reward systems for mentoring. Support from mentors was thought to be limited in terms of targeted scientific guidance and long-term commitments to the relationship. Most of the participants expressed concerns about how they could secure the next level of funding with diminishing confidence. Notably, the work-life balance was neither conceptualised as a 'barrier' to successful pursuit of research career nor was it translated into the reason for leaving the dual clinical-research career pathway. CONCLUSIONS:Results revealed specific limitations presented by the research environment in newly emerging Asian AMCs. To retain a vibrant clinician-scientist workforce, additional measures are needed, aiming to improve institutional culture of research, build mentoring networks, adopt effective tools for tracking career progress and provide a clear and viable career progression path for clinician-scientist. Further research might explore the cross-cultural differences in managing work-life balance in academic medicine.
| S-EPMC5855163 | biostudies-literature
Project description:The risk-characterization of chemicals requires the determination of repeated-dose toxicity (RDT). This depends on two main outcomes: the no-observed-adverse-effect level (NOAEL) and the lowest-observed-adverse-effect level (LOAEL). These endpoints are fundamental requirements in several regulatory frameworks, such as the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) and the European Regulation of 1223/2009 on cosmetics. The RDT results for the safety evaluation of chemicals are undeniably important; however, the in vivo tests are time-consuming and very expensive. The in silico models can provide useful input to investigate sub-chronic RDT. Considering the complexity of these endpoints, involving variable experimental designs, this non-testing approach is challenging and attractive. Here, we built eight in silico models for the NOAEL and LOAEL predictions, focusing on systemic and organ-specific toxicity, looking into the effects on the liver, kidney and brain. Starting with the NOAEL and LOAEL data for oral sub-chronic toxicity in rats, retrieved from public databases, we developed and validated eight quantitative structure-activity relationship (QSAR) models based on the optimal descriptors calculated by the Monte Carlo method, using the CORAL software. The results obtained with these models represent a good achievement, to exploit them in a safety assessment, considering the importance of organ-related toxicity.
| S-EPMC9224506 | biostudies-literature
Project description:Quantitative Structure-Activity Relationship (QSAR) models are commonly used for risk assessment of emerging contaminants. The objective of this study was to use a toxicity rank order (TRO) as an integrating parameter to improve the toxicity prediction by QSAR models. TRO for each contaminant was calculated from collected toxicity data including acute toxicity concentration and no observed effect concentration. TRO values associated with toxicity mechanisms were used to classify pollutants into three modes of action consisting of narcosis, transition and reactivity. The selection principle of parameters for QSAR models was established and verified. It showed a reasonable prediction of toxicities caused by organophosphates and benzene derivatives, especially. Compared with traditional procedures, incorporating TRO showed an improved correlation coefficient of QSAR models by approximately 10%. Our study indicated that the proposed procedure can be used for screening modeling parameter data and improve the toxicity prediction by QSAR models, and this could facilitate prediction and evaluation of environmental contaminant toxicity.
| S-EPMC9819504 | biostudies-literature