From the article: Abstract Sub-chronic toxicity studies of 163 non-genotoxic chemicals were evaluated in order to predict the tumour outcome of 24-month rat carcinogenicity studies obtained from the EFSA and ToxRef databases. Hundred eleven of the 148 chemicals that did not induce putative preneoplastic lesions in the sub-chronic study also did not induce tumours in the carcinogenicity study (True Negatives). Cellular hypertrophy appeared to be an unreliable predictor of carcinogenicity. The negative predictivity, the measure of the compounds evaluated that did not show any putative preneoplastic lesion in de sub-chronic studies and were negative in the carcinogenicity studies, was 75%, whereas the sensitivity, a measure of the sub-chronic study to predict a positive carcinogenicity outcome was only 5%. The specificity, the accuracy of the sub-chronic study to correctly identify non-carcinogens was 90%. When the chemicals which induced tumours generally considered not relevant for humans (33 out of 37 False Negatives) are classified as True Negatives, the negative predictivity amounts to 97%. Overall, the results of this retrospective study support the concept that chemicals showing no histopathological risk factors for neoplasia in a sub-chronic study in rats may be considered non-carcinogenic and do not require further testing in a carcinogenicity study.
Semen traces are considered important pieces of evidence in forensic investigations, especially those involving sexsual offenses. Recently, our research group developed a fluorescence-based technique to accurately determine the age of semen traces. However, the specific compounds resonsible for the fluoresescent behaviour of ageing semens remain unknown. As such, in this exploratory study, the aim is to identify the components associated with the fluorescent behavior of ageing semen traces. In this investigation semen stains and various biofluorophores commonly found in body fluids were left to aged for 0, 2, 4, 7, 14 and 21 days. Subsequently, thin-layer chromatography (TLC) and ultra-performance liquid chromatography (UPLC) mass spectrometry were performed to identify the biofluorophores present in semen. Several contributors to the autofluorescence could be identified in semen stain, these include tryptophan, kynurenine, kynurenic acid, and norharman. The study sheds light on the.
To study the ways in which compounds can induce adverse effects, toxicologists have been constructing Adverse Outcome Pathways (AOPs). An AOP can be considered as a pragmatic tool to capture and visualize mechanisms underlying different types of toxicity inflicted by any kind of stressor, and describes the interactions between key entities that lead to the adverse outcome on multiple biological levels of organization. The construction or optimization of an AOP is a labor intensive process, which currently depends on the manual search, collection, reviewing and synthesis of available scientific literature. This process could however be largely facilitated using Natural Language Processing (NLP) to extract information contained in scientific literature in a systematic, objective, and rapid manner that would lead to greater accuracy and reproducibility. This would support researchers to invest their expertise in the substantive assessment of the AOPs by replacing the time spent on evidence gathering by a critical review of the data extracted by NLP. As case examples, we selected two frequent adversities observed in the liver: namely, cholestasis and steatosis denoting accumulation of bile and lipid, respectively. We used deep learning language models to recognize entities of interest in text and establish causal relationships between them. We demonstrate how an NLP pipeline combining Named Entity Recognition and a simple rules-based relationship extraction model helps screen compounds related to liver adversities in the literature, but also extract mechanistic information for how such adversities develop, from the molecular to the organismal level. Finally, we provide some perspectives opened by the recent progress in Large Language Models and how these could be used in the future. We propose this work brings two main contributions: 1) a proof-of-concept that NLP can support the extraction of information from text for modern toxicology and 2) a template open-source model for recognition of toxicological entities and extraction of their relationships. All resources are openly accessible via GitHub (https://github.com/ontox-project/en-tox).
Chemical preservation is an important process that prevents foods, personal care products, woods and household products, such as paints and coatings, from undesirable change or decomposition by microbial growth. To date, many different chemical preservatives are commercially available, but they are also associated with health threats and severe negative environmental impact. The demand for novel, safe, and green chemical preservatives is growing, and this process is further accelerated by the European Green Deal. It is expected that by the year of 2050 (or even as soon as 2035), all preservatives that do not meet the ‘safe-by-design’ and ‘biodegradability’ criteria are banned from production and use. To meet these European goals, there is a large need for the development of green, circular, and bio-degradable antimicrobial compounds that can serve as alternatives for the currently available biocidals/ preservatives. Anthocyanins, derived from fruits and flowers, meet these sustainability goals. Furthermore, preliminary research at the Hanze University of Applied Science has confirmed the antimicrobial efficacy of rose and tulip anthocyanin extracts against an array of microbial species. Therefore, these molecules have the potential to serve as novel, sustainable chemical preservatives. In the current project we develop a strategy consisting of fractionation and state-of-the-art characterization methods of individual anthocyanins and subsequent in vitro screening to identify anthocyanin-molecules with potent antimicrobial efficacy for application in paints, coatings and other products. To our knowledge this is the first attempt that combines in-depth chemical characterization of individual anthocyanins in relation to their antimicrobial efficacy. Once developed, this strategy will allow us to single out anthocyanin molecules with antimicrobial properties and give us insight in structure-activity relations of individual anthocyanins. Our approach is the first step towards the development of anthocyanin molecules as novel, circular and biodegradable non-toxic plant-based preservatives.
The valorization of biowaste, by exploiting side stream compounds as feedstock for the sustainable production of bio-based materials, is a key step towards a more circular economy. In this regard, chitin is as an abundant resource which is accessible as a waste compound of the seafood industry. From a commercial perspective, chitin is chemically converted into chitosan, which has multiple industrial applications. Although the potential of chitin has long been established, the majority of seafood waste containing chitin is still left unused. In addition, current processes which convert chitin into chitosan are sub-optimal and have a significant impact on the environment. As a result, there is a need for the development of innovative methods producing bio-based products from chitin. This project wants to contribute to these challenges by performing a feasibility study which demonstrates the microbial bioconversion of chitin to polyhydroxyalkanoates (PHAs). Specifically, the consortium will attempt to cultivate and engineer a recently discovered bacterium Chi5, so that it becomes able to directly produce PHAs from chitin present in solid shrimp shell waste. If successful, this project will provide a proof-of-concept for a versatile microbial production platform which can contribute to: i) the valorization of biowaste from the seafood industry, ii) the efficient utilization of chitin as feedstock, iii) the sustainable and (potentially low-cost) production of PHAs. The project consortium is composed of: i) Van Belzen B.V., a Dutch shrimp trading company which are highly interested in the valorization of their waste streams, hereby making their business model more profitable and sustainable. ii) AMIBM, which have recently isolated and characterized the Chi5 marine-based chitinolytic bacterium and iii) Zuyd, which will link aforementioned partners with students in creating a novel collaboration which will stimulate the development of students and the translation of academic knowledge to a feasible application technology for SME’s.
On a yearly basis 120 million kg of spent coffee ground (SCG) is disposed as waste. Two partners in the project have the intension to refine the valuable compounds from this coffee residue. One of these compounds is the group of melanoidins. It is proven that these natural polymers, with polyphenols incorporated, can be applied as colourant to textiles. These colourant compounds can be extracted from the SCG. In this project an industrial feasible dye recipe for SCG extract to cotton will be developed. This twostep dye method consists of a mordanting step and a colour uptake step. Both will be optimised to colour intensity and light and wash fastness. Parameters as cycle time and energy and water consumption, will be take into account to make the dye recipe applicable for industrial standards. Chemical analysis of mordant compounds (tannins) and colourants (polyphenols) will be carried out to quantify and qualify the uptake by cotton. With the results of this project, the partners will be able to support their customers of the SCG extract with a scientific based advise about the application as a textile dye to ensure a solid market acceptance of SCG extract. With the SCG extract as a professional biobased colorant in the market, companies in textile industry will have a wider choice in using environmental friendly products. At the end, this will lead to complete biodegradable products for consumers.
