A Review of Toxicological Profile of Fentanyl—A 2024 Update

Fentanyl and its analogues are synthetic opioids of varying potencies that are unfortunately heavily abused. Over the last 15 years, fentanyl and its analogues have contributed to the increasing prominence of hospitalisation and numerous deaths due to drug overdose. In this comprehensive literature review, the mechanism of toxicity of the drug in humans is evaluated. A systematic approach was used whereby the relevant literature has been detailed where the toxicity of fentanyl and/or its analogues to different organs/systems were investigated. Furthermore, the review covers the post-mortem toxicological data and demographic information from past fatal cases where fentanyl was believed to be involved. Such insight into fentanyl toxicity is useful as an aid to better understand the toxic doses of the drug and the suspected mechanism of action and the unexpected complications associated with overdose incidences involving the drug. Finally, the review offers an overview of the traditional and emerging test systems used to investigate the adverse effects of fentanyl on human health

The intestinal expulsion of the roundworm Ascaris suum is associated with eosinophils, intra-epithelial T cells and decreased intestinal transit time

Ascaris lumbricoides remains the most common endoparasite in humans, yet there is still very little information available about the immunological principles of protection, especially those directed against larval stages. Due to the natural host-parasite relationship, pigs infected with A. suum make an excellent model to study the mechanisms of protection against this nematode. In pigs, a self-cure reaction eliminates most larvae from the small intestine between 14 and 21 days post infection. In this study, we investigated the mucosal immune response leading to the expulsion of A. suum and the contribution of the hepato-tracheal migration. Self-cure was independent of previous passage through the liver or lungs, as infection with lung stage larvae did not impair self-cure. When animals were infected with 14-day-old intestinal larvae, the larvae were being driven distally in the small intestine around 7 days post infection but by 18 days post infection they re-inhabited the proximal part of the small intestine, indicating that more developed larvae can counter the expulsion mechanism. Self-cure was consistently associated with eosinophilia and intra-epithelial T cells in the jejunum. Furthermore, we identified increased gut movement as a possible mechanism of self-cure as the small intestinal transit time was markedly decreased at the time of expulsion of the worms. Taken together, these results shed new light on the mechanisms of self-cure that occur during A. suum infections

AIMS: An Automatic Semantic Machine Learning Microservice Framework to Support Biomedical and Bioengineering Research

The fusion of machine learning and biomedical research offers novel ways to understand, diagnose, and treat various health conditions. However, the complexities of biomedical data, coupled with the intricate process of developing and deploying machine learning solutions, often pose significant challenges to researchers in these fields. Our pivotal achievement in this research is the introduction of the Automatic Semantic Machine Learning Microservice Framework (AIMS). AIMS addresses these challenges by automating various stages of the machine learning pipeline, with a particular emphasis on the ontology of machine learning services tailored for the biomedical domain. This ontology encompasses everything from task representation, service modeling, and knowledge acquisition to knowledge reasoning and the establishment of a self-supervised learning policy. Our framework has been crafted to prioritize model interpretability, integrate domain knowledge effortlessly, and handle biomedical data with efficiency. Additionally, AIMS boasts a distinctive feature: it leverages self-supervised knowledge learning through reinforcement learning techniques, paired with an ontology-based policy recording schema. This enables it to autonomously generate, fine-tune, and continually adapt to machine learning models, especially when faced with new tasks and data. Our work has two standout contributions of demonstrating that machine learning processes in the biomedical domain can be automated, while integrating a rich domain knowledge base and providing a way for machines to have a self-learning ability, ensuring they handle new tasks effectively. To showcase AIMS in action, we've highlighted its prowess in three case studies from biomedical tasks. These examples emphasize how our framework can simplify research routines, uplift the caliber of scientific exploration, and set the stage for notable advances

Co-Culture of Gut Bacteria and Metabolite Extraction Using Fast Vacuum Filtration and Centrifugation

This protocol describes a robust method for the extraction of intra and extracellular metabolites of gut bacterial mono and co-cultures. In recent years, the co-culture techniques employed in the field of microbiology have demonstrated significant importance in regard to understanding cell–cell interactions, cross-feeding, and the metabolic interactions between different bacteria, fungi, and microbial consortia which enable the mimicking of complex co-habitant conditions. This protocol highlights a robust reproducible physiologically relevant culture and extraction protocol for the co-culture of gut bacterium. The novel extraction steps are conducted without using quenching and cell disruption through bead-cell methods, freeze–thaw cycles, and sonication, which tend to affect the physical and biochemical properties of intracellular metabolites and secretome. The extraction procedure of inoculated bacterial co-cultures and monocultures use fast vacuum filtration and centrifugation. The extraction methodology is fast, effective, and robust, requiring 4 h to complete

Nanotoxicology

As the production and use of nanomaterials (NMs) in medicine and many other applications develops, so the need to understand the potential risks posed by NMs to human health (and the environment) increases (Aitken et al. 2006). At the nanoscale (1-100 nm), materials exhibit properties that are different to larger or bulk materials. These new properties are exploited by researchers and industry to generate new products; however, the same properties can also inuence how the NM behaves in biological systems, including affecting toxicity. Nanotoxicology is a relatively new eld of research that aims to assess the human and environmental hazard of nanomaterials. In recent years, this new discipline has seen a rapid expansion in the number of studies concerned with assessing the safety of engineered NMs (Figure 20.1)

A comprehensive toxicological analysis of panel of unregulated e-cigarettes to human health

Electronic cigarettes, commonly referred to as e-cigarettes have gained popularity over recent years especially among young individuals. In the light of the escalating prevalence of the use of these products and their potential for long-term health effects, in this study as the first of its kind a comprehensive toxicological profiling of the liquid from a panel of unregulated e-cigarettes seized in the UK was undertaken using an in vitro co-culture model of the upper airways. The data showed that e-cigarettes caused a dose dependent increase in cell death and inflammation manifested by enhanced release of IL1ß and IL6. Furthermore, the e-cigarettes induced oxidative stress as demonstrated by a reduction of intracellular glutathione and an increase in generation of reactive oxygen species. Moreover, the assessment of genotoxicity showed significant DNA strand breaks (following exposure to Tigerblood flavoured e-cigarette). Moreover, relevant to the toxicological observations, was the detection of varying and frequently high levels of hazardous metals including cadmium, copper, nickel and lead. This study highlights the importance of active and ongoing collaborations between academia, governmental organisations and policy makers (Trading standards, Public Health) and national health service in tackling vape addiction and better informing the general public regarding the risks associated with e-cigarette usage

Polylactic is a Sustainable, Low Absorption, Low Autofluorescence Alternative to Other Plastics for Microfluidic and Organ-on-Chip Applications

Organ-on-chip (OOC) devices are miniaturized devices replacing animal models in drug discovery and toxicology studies. The majority of OOC devices are made from polydimethylsiloxane (PDMS), an elastomer widely used in microfluidic prototyping, but posing a number of challenges to experimentalists, including leaching of uncured oligomers and uncontrolled absorption of small compounds. Here we assess the suitability of polylactic acid (PLA) as a replacement material to PDMS for microfluidic cell culture and OOC applications. We changed the wettability of PLA substrates and demonstrated the functionalization method to be stable over a time period of at least 9 months. We successfully cultured human cells on PLA substrates and devices, without coating. We demonstrated that PLA does not absorb small molecules, is transparent (92% transparency), and has low autofluorescence. As a proof of concept of its manufacturability, biocompatibility, and transparency, we performed a cell tracking experiment of prostate cancer cells in a PLA device for advanced cell culture

Assessing the transferability and reproducibility of 3D in vitro liver models from primary human multi-cellular microtissues to cell-line based HepG2 spheroids

To reduce, replace, and refine in vivo testing, there is increasing emphasis on the development of more physiologically relevant in vitro test systems to improve the reliability of non-animal-based methods for hazard assessment. When developing new approach methodologies, it is important to standardize the protocols and demonstrate the methods can be reproduced by multiple laboratories. The aim of this study was to assess the transferability and reproducibility of two advanced in vitro liver models, the Primary Human multicellular microtissue liver model (PHH) and the 3D HepG2 Spheroid Model, for nanomaterial (NM) and chemical hazard assessment purposes. The PHH model inter-laboratory trial showed strong consistency across the testing sites. All laboratories evaluated cytokine release and cytotoxicity following exposure to titanium dioxide (TiO2) and zinc oxide (ZnO) nanoparticles. No significant difference was observed in cytotoxicity or IL-8 release for the test materials. The data were reproducible with all three laboratories with control readouts within a similar range. The PHH model ZnO induced the greatest cytotoxicity response at 50.0 μg/mL and a dose-dependent increase in IL-8 release. For the 3D HepG2 spheroid model, all test sites were able to construct the model and demonstrated good concordance in IL-8 cytokine release and genotoxicity data. This trial demonstrates the successful transfer of new approach methodologies across multiple laboratories, with good reproducibility for several hazard endpoints.Toxicolog

The application of existing genotoxicity methodologies for grouping of nanomaterials: Towards an integrated approach to testing and assessment.

The incorporation of nanomaterials (NMs) in consumer products has proven to be highly valuable in many sectors. Unfortunately, however, the same nano specific physicochemical properties, which make these material attractive, might also contribute to hazards for people exposed to these materials. The physicochemical properties of NMs will impact their interaction with biological surroundings and influence their fate and their potential adverse effects such as genotoxicity. Due to the large and expanding number of NMs produced, their availability in different nanoforms (NFs) and their utilization in various formats, it is impossible for risk assessment to be conducted on an individual NF basis. Alternative methods, such as grouping are needed for streamlining hazard assessment. The GRACIOUS Framework provides a logical and science evidenced approach to group similar NFs, allowing read-across of hazard information from source NFs (or non-NFs) with adequate hazard data to target NFs that lack such data. Here, we propose a simple three-tiered testing strategy to gather evidence to determine whether different NFs are sufficiently similar with respect to their potential to induce genotoxicity, in order to be grouped. The tiered testing strategy includes simple in vitro models as well as a number of alternative more complex multi-cellular in vitro models to allow for a better understanding of secondary NM-induced DNA damage, something that has been more appropriate in vivo until recently