A comparison of transgenic rodent mutation and in vivo comet assay responses for 91 chemicals.

A database of 91 chemicals with published data from both transgenic rodent mutation (TGR) and rodent comet assays has been compiled. The objective was to compare the sensitivity of the two assays for detecting genotoxicity. Critical aspects of study design and results were tabulated for each dataset. There were fewer datasets from rats than mice, particularly for the TGR assay, and therefore, results from both species were combined for further analysis. TGR and comet responses were compared in liver and bone marrow (the most commonly studied tissues), and in stomach and colon evaluated either separately or in combination with other GI tract segments. Overall positive, negative, or equivocal test results were assessed for each chemical across the tissues examined in the TGR and comet assays using two approaches: 1) overall calls based on weight of evidence (WoE) and expert judgement, and 2) curation of the data based on a priori acceptability criteria prior to deriving final tissue specific calls. Since the database contains a high prevalence of positive results, overall agreement between the assays was determined using statistics adjusted for prevalence (using AC1 and PABAK). These coefficients showed fair or moderate to good agreement for liver and the GI tract (predominantly stomach and colon data) using WoE, reduced agreement for stomach and colon evaluated separately using data curation, and poor or no agreement for bone marrow using both the WoE and data curation approaches. Confidence in these results is higher for liver than for the other tissues, for which there were less data. Our analysis finds that comet and TGR generally identify the same compounds (mainly potent mutagens) as genotoxic in liver, stomach and colon, but not in bone marrow. However, the current database content precluded drawing assay concordance conclusions for weak mutagens and non-DNA reactive chemicals

Marked Changes in Gut Microbiota in Cardio-Surgical Intensive Care Patients:A Longitudinal Cohort Study

Background: Virtually no studies on the dynamics of the intestinal microbiota in patients admitted to the intensive care unit (ICU) are published, despite the increasingly recognized important role of microbiota on human physiology. Critical care patients undergo treatments that are known to influence the microbiota. However, dynamics and extent of such changes are not yet fully understood. To address this topic, we analyzed the microbiota before, during and after planned major cardio surgery that, for the first time, allowed us to follow the microbial dynamics of critical care patients. In this prospective, observational, longitudinal, single center study, we analyzed the fecal microbiota using 16S rRNA gene sequencing. Results: Samples of 97 patients admitted between April 2015 and November 2016 were included. In 32 patients, data of all three time points (before, during and after admission) were available for analysis. We found a large intra-individual variation in composition of gut microbiota. During admission, a significant change in microbial composition occurred in most patients, with a significant increase in pathobionts combined with a decrease in strictly anaerobic gut bacteria, typically beneficial for health. A lower bacterial diversity during admission was associated with longer hospitalization. In most patients analyzed at all three time points, the change in microbiota during hospital stay reverted to the original composition post-discharge. Conclusions: Our study shows that, even with a short ICU stay, patients present a significant change in microbial composition shortly after admission. The unique longitudinal setup of this study displayed a restoration of the microbiota in most patients to baseline composition post-discharge, which demonstrated its great restorative capacity. A relative decrease in benign or even beneficial bacteria and increase of pathobionts shifts the microbial balance in the gut, which could have clinical relevance. In future studies, the microbiota of ICU patients should be considered a good target for optimisation

Cell transformation assays for prediction of carcinogenic potential: State of the science and future research needs

Copyright @ 2011 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.Cell transformation assays (CTAs) have long been proposed as in vitro methods for the identification of potential chemical carcinogens. Despite showing good correlation with rodent bioassay data, concerns over the subjective nature of using morphological criteria for identifying transformed cells and a lack of understanding of the mechanistic basis of the assays has limited their acceptance for regulatory purposes. However, recent drivers to find alternative carcinogenicity assessment methodologies, such as the Seventh Amendment to the EU Cosmetics Directive, have fuelled renewed interest in CTAs. Research is currently ongoing to improve the objectivity of the assays, reveal the underlying molecular changes leading to transformation and explore the use of novel cell types. The UK NC3Rs held an international workshop in November 2010 to review the current state of the art in this field and provide directions for future research. This paper outlines the key points highlighted at this meeting

Development and evaluation of uncertainty quantifying machine learning models to predict piperacillin plasma concentrations in critically ill patients

Background: Beta-lactam antimicrobial concentrations are frequently suboptimal in critically ill patients. Population pharmacokinetic (PopPK) modeling is the golden standard to predict drug concentrations. However, currently available PopPK models often lack predictive accuracy, making them less suited to guide dosing regimen adaptations. Furthermore, many currently developed models for clinical applications often lack uncertainty quantification. We, therefore, aimed to develop machine learning (ML) models for the prediction of piperacillin plasma concentrations while also providing uncertainty quantification with the aim of clinical practice. Methods: Blood samples for piperacillin analysis were prospectively collected from critically ill patients receiving continuous infusion of piperacillin/tazobactam. Interpretable ML models for the prediction of piperacillin concentrations were designed using CatBoost and Gaussian processes. Distribution-based Uncertainty Quantification was added to the CatBoost model using a proposed Quantile Ensemble method, useable for any model optimizing a quantile function. These models are subsequently evaluated using the distribution coverage error, a proposed interpretable uncertainty quantification calibration metric. Development and internal evaluation of the ML models were performed on the Ghent University Hospital database (752 piperacillin concentrations from 282 patients). Ensuing, ML models were compared with a published PopPK model on a database from the University Medical Centre of Groningen where a different dosing regimen is used (46 piperacillin concentrations from 15 patients.). Results: The best performing model was the Catboost model with an RMSE and R-2 of 31.94-0.64 and 33.53-0.60 for internal evaluation with and without previous concentration. Furthermore, the results prove the added value of the proposed Quantile Ensemble model in providing clinically useful individualized uncertainty predictions and show the limits of homoscedastic methods like Gaussian Processes in clinical applications. Conclusions: Our results show that ML models can consistently estimate piperacillin concentrations with acceptable and high predictive accuracy when identical dosing regimens as in the training data are used while providing highly relevant uncertainty predictions. However, generalization capabilities to other dosing schemes are limited. Notwithstanding, incorporating ML models in therapeutic drug monitoring programs seems definitely promising and the current work provides a basis for validating the model in clinical practice

ECVAM retrospective validation of in vitro micronucleus test (MNT)

In the past decade several studies comparing the in vitro chromosome aberration test (CAT) and the in vitro micronucleus test (MNT) were performed. A high correlation was observed in each of the studies (>85%); however, no formal validation for the micronucleus in vitro assay had been carried out. Therefore, a working group was established by the European Centre for the Validation of Alternative Methods (ECVAM) to perform a retrospective validation of the existing data, in order to evaluate the validity of the in vitro MNT on the basis of the modular validation approach. The primary focus of this retrospective validation was on the evaluation of the potential of the in vitro MNT as alternative to the standard in vitro CAT. The working group evaluated, in a first step, the available published data and came to the conclusion that two studies [German ring trial, von der Hude, W., Kalweit, S., Engelhardt, G. et al. (2000) In-vitro micronucleus assay with Chinese hamster V79 cells: results of a collaborative study with 26 chemicals. Mutat. Res., 468, 137–163, and SFTG International Collaborative Study, Lorge, E., Thybaud, V., Aardema, M., Oliver, J., Wataka, A., Lorenzon, G. and Marzin, D. (2006) SFTG International Collaborative Study on in-vitro micronucleus test I. General conditions and overall conclusions of the study. Mutat. Res., 607, 13–36] met the criteria for a retrospective validation according to the criteria previously defined by the working group. These two studies were evaluated in depth (including the reanalysis of raw data) and provided the information required for assessing the reliability (reproducibility) of the test. For the assessment of the concordance between the in vitro MNT and the in vitro CAT, additional published data were considered. Based on this retrospective validation, the ECVAM Validation Management Team concluded that the in vitro MNT is reliable and relevant and can therefore be used as an alternative method to the in vitro CAT. Following peer review, these conclusions were formally endorsed by the ECVAM Scientific Advisory Committee

Characterization of bovine embryos cultured under conditions appropriate for sustaining human naïve pluripotency.

In mammalian preimplantation development, pluripotent cells are set aside from cells that contribute to extra-embryonic tissues. Although the pluripotent cell population of mouse and human embryos can be cultured as embryonic stem cells, little is known about the pathways involved in formation of a bovine pluripotent cell population, nor how to maintain these cells in vitro. The objective of this study was to determine the transcriptomic profile related to bovine pluripotency. Therefore, in vitro derived embryos were cultured in various culture media that recently have been reported capable of maintaining the naïve pluripotent state of human embryonic cells. Gene expression profiles of embryos cultured in these media were compared using microarray analysis and quantitative RT-PCR. Compared to standard culture conditions, embryo culture in 'naïve' media reduced mRNA expression levels of the key pluripotency markers NANOG and POU5F1. A relatively high percentage of genes with differential expression levels were located on the X-chromosome. In addition, reduced XIST expression was detected in embryos cultured in naïve media and female embryos contained fewer cells with H3K27me3 foci, indicating a delay in X-chromosome inactivation. Whole embryos cultured in one of the media, 5iLA, could be maintained until 23 days post fertilization. Together these data indicate that 'naïve' conditions do not lead to altered expression of known genes involved in pluripotency. Interestingly, X-chromosome inactivation and development of bovine embryos were dependent on the culture conditions

Elevated Non-Esterified Fatty Acid Concentrations during Bovine Oocyte Maturation Compromise Early Embryo Physiology

Elevated concentrations of serum non-esterified fatty acids (NEFA), associated with maternal disorders such as obesity and type II diabetes, alter the ovarian follicular micro-environment and have been associated with subfertility arising from reduced oocyte developmental competence. We have asked whether elevated NEFA concentrations during oocyte maturation affect the development and physiology of zygotes formed from such oocytes, using the cow as a model. The zygotes were grown to blastocysts, which were evaluated for their quality in terms of cell number, apoptosis, expression of key genes, amino acid turnover and oxidative metabolism. Oocyte maturation under elevated NEFA concentrations resulted in blastocysts with significantly lower cell number, increased apoptotic cell ratio and altered mRNA abundance of DNMT3A, IGF2R and SLC2A1. In addition, the blastocysts displayed reduced oxygen, pyruvate and glucose consumption, up-regulated lactate consumption and higher amino acid metabolism. These data indicate that exposure of maturing oocytes to elevated NEFA concentrations has a negative impact on fertility not only through a reduction in oocyte developmental capacity but through compromised early embryo quality, viability and metabolism