The glucagon-like peptide 1 receptor (GLP-1R) is a member of the family (or class) B G-protein-coupled receptor (GPCR). The receptor is a regulator of insulin and a key target in treating Type 2 diabetes mellitus. In this investigation, computational chemistry techniques such as molecular docking were combined with in silico ADME/Tox predictions to determine the position and structure of the allosteric binding site, as well as to examine how the allosteric modulators bind to the binding site. In silico evaluation was used to evaluate the ADME/Tox properties of the allosteric modulators. The findings of the ligand docking studies suggest that the allosteric binding site is situated around the transmembrane (TM) domain TM 6 of the receptor in the active state. ADME/Tox characterisation of the allosteric modulators demonstrate that compounds 1–3 (2,6,7-trichloro-3-(trifluoromethyl)quinoxaline, 1-(5-(4-(tert-butyl)phenyl)-1,3,4-oxadiazol-2-yl)-6,6-dimethyl-3-(methylsulfonyl)-6,7-dihydrobenzo[c]thiophen-4(5H)-one, 2-((4-chlorophenyl)thio)-3-(trifluoromethyl)quinoxaline, respectively) complied with the traditional method of evaluating drug-likeness; Lipinski’s rule of 5. The allosteric modulator compound 4 (3-(8-chloro-6-(trifluoromethyl)imidazo[1,2-a]pyridin-2-yl)phenyl cyclohexanecarboxylate) failed to comply with Lipinski’s rule of five as a result of having a logP value of over 5.6. Moreover, molecular docking studies provide insights into potential allosteric binding sites and possible interactions. Finally, the in silico ADME/Tox study results are described as relevant to developing a viable drug candidate.

Objective: The use of benchtop metabolic profiling technology based on nuclear magnetic resonance (NMR) was evaluated in a small cohort of cats with a view to applying this as a viable and rapid metabolic tool to support clinical decision making. Results: Urinary metabolites were analysed from four subjects consisting of two healthy controls and two chronic kidney disease (CKD) IRIS stage 2 cases. The study identified 15 metabolites in cats with CKD that were different from the controls. Among them were acetate, creatinine, citrate, taurine, glycine, serine and threonine. Benchtop NMR technology is capable of distinguishing between chronic kidney disease case and control samples in a pilot feline cohort based on metabolic profile. We offer perspectives on the further development of this pilot work and the potential of the technology, when combined with sample databases and computational intelligence techniques to offer a clinical decision support tool not only for cases of renal disease but other metabolic conditions in the future.

Background: The early detection of cancer remains a critical challenge in clinical oncology, with significant implications for patient survival rates and treatment outcomes. Research focus has shifted to developing minimally invasive diagnostic approaches for cancer detection and prognosis, such as metabolomic analysis of biological fluids and tumour-derived components, including extracellular vesicles (EVs). EVs carry molecular cargo, including metabolites, that reflect the pathophysiological state of their cell of origin. Analysis and characterisation of these metabolites may offer novel insights into cancer biology and facilitate the identification of potential biomarkers. Aim of review: This review systematically examines existing literature on the metabolomic analysis of EVs in the context of cancer to obtain a deeper understanding of potential metabolite biomarkers associated with cancer. Key scientific concepts of review: A comprehensive search of PubMed, Scopus, and Web of Science was conducted using a defined strategy to identify studies analysing EV-derived metabolites in cancer. Twelve eligible studies were included, collectively reporting 1,602 identified metabolites across various cancer types, sample sources, EV isolation methods, and metabolomic techniques. Of these, 333 metabolites were reported to be differentially regulated in EVs derived from patients with cancer, or conditioned medium from cancerous cell lines and their respective healthy controls. The review highlights the potential of EV metabolomics to detect cancer biomarkers but also underscores methodological variability as a major limitation. Differences in isolation and analytical techniques likely contribute to inconsistent findings, emphasising the need for standardised protocols in future research.

UV irradiation has shown potential in reducing bacterial and viral loadings. This is a pilot study aimed at investigating the antimicrobial effect of a novel pulsed UVA and UVC technology on bacteria and human coronavirus 229E. The selection of these microorganisms is based on their relevance and significance in real-world scenarios. This study consists of independent experiments for the assessment of antibacterial and antiviral activities by using a lawn plate approach, measuring levels of adenine triphosphate (ATP) in three bacterial strains, Escherichia coli, Staphylococcus epidermidis and Bacillus subtilis, and performing Median Tissue Culture Infectious Dose (TCID₅₀) of HCoV-229E on MRC-5 human lung fibroblast cell line. The results demonstrated the ability of UVA and UVC irradiation to reduce levels of adenine triphosphate (ATP) over a 12 h exposure period in all three bacterial strains, comparative to dark and artificial/natural light conditions using non-pulsing experiments. In addition to this, there was a reduction in colonies exposed to UVA and UVC pulsing experiments for E. coli K12 and S. epidermis compared to bacteria stored in artificial/natural and dark conditions. Furthermore, using dose-dependent modelling, it was demonstrated that the cross-contamination risk was reduced by 50% using E. coli as a typical model. Regarding the antiviral assay, the results showed that TCID₅₀ of HCoV-229E was reduced after the first cycle of UV engagement. No cytopathic effect (CPE) was detected after three cycles using Protocol 1. The findings showed that UVA and UVC were effective under the conditions outlined in this paper for a reduction in the number of bacteria with additional applications to viruses.

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Due to the aromatase enzyme’s involvement in estrogen biosynthesis, aromatase inhibitors have emerged as the preferred treatment for postmenopausal women with ER+ breast cancer. Using computational chemistry tools, we investigate how the human placental aromatase cytochrome P450 interacts with various phorbols with distinct chains at C-12, C-13, and C-20, as well as the well-known aromatase inhibitors anastrozole, exemestane, and letrozole. To identify phorbol-aromatase interactions, we performed a protein–ligand docking using the structures of our ligands and proteins using the Flare software (version 2.0, Cresset Software, Litlington, UK). These preliminary findings show that the phorbols considered (P-12,13-diAcPh, P-12,13-diiBu, P-12AcPh-13iBu, P-12Ang-13iBu, P-20Ac-12AcPh-13iBu and P-20Ac-12Ang-13iBu) had the highest binding energies in comparison with the commercially available aromatase inhibitors (anastrozole, letrozole, exemestane) used in this study. A subset of the previously described binding residues of testosterone (TST), the endogenous ligand, were also found to be responsible for the phorbol diesters’ binding to the aromatase enzyme, as demonstrated by the findings. This further suggests that the phorbol diesters can bind efficiently to CYP19A1 and may be able to alter its activity because they had higher binding energies than the commercially available drugs.