https://www.um.edu.mt/library/oar/handle/123456789/16097 Thu, 23 Jul 2026 04:34:37 GMT 2026-07-23T04:34:37Z https://www.um.edu.mt/library/oar/handle/123456789/148117 Title: Advancing microRNA target site identification via bias-corrected chimeric datasets for machine learning approaches Abstract: microRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression post-transcriptionally. These ∼22-nucleotide long RNA molecules are loaded onto a protein of the Argonaute (AGO) family guiding it to specific RNA target transcripts, which are consequently inhibited from translation to protein. Despite years of research, the precise mechanisms that determine miRNA target recognition remain unclear. Given that a single miRNA can potentially target any RNA transcript, experimental validation of all possible interactions is impractical. To this end, with the recent availability of volumes of data from high-throughput CLASH experiments that capture interacting RNA molecules mediated by a protein, many miRNA target site prediction methods employing data-driven approaches have been developed. However, despite substantial efforts to produce more accurate models, currently, no standardised framework for benchmarking miRNA target site prediction methods exists, and various strategies have been adopted, hindering fair and reliable comparison. Consequently, this undermines the validity of performance claims. Recently, another high-throughput experimental technique, called chimeric eCLIP, was developed, leading to a 70-fold increase in the recovery of miRNA– target site interactions. Here, we identify a unique opportunity to leverage this immense resource of publicly available raw data, to curate benchmark datasets for miRNA target site prediction. Throughout this work, we additionally uncover a miRNA frequency class bias that arises as a result of the method used to generate negative examples in silico. Such methods are required when modeling miRNA target site prediction as a supervised binary classification problem, due to the absence of experimentally confirmed non-binding miRNA–target pairs. To this end, we develop a novel method for generating negatives that mitigates the identified bias. Leveraging data from these high-throughput experiments and applying this new method for generating negatives, we curate three collections of datasets: one novel dataset containing almost three million examples, and bias-corrected versions of two smaller, published datasets. We contribute these datasets to the publicly available and easy-to-use miRBench Python package, providing a framework for benchmarking miRNA target site prediction methods. We benchmark six state-of-the-art deep learning models on these datasets and train simple models to establish a baseline. Retraining a convolutional neural network, that was originally trained on a biased dataset (Average Precision Score (APS): 0.71), on a larger, bias-corrected dataset improves its performance (APS: 0.81), surpassing the previous state of the art (TargetScanCnn, APS: 0.76). This highlights the advantages of well-curated, unbiased benchmarks, facilitating the development of more accurate miRNA target site prediction models thus enabling more reliable downstream analyses. Description: M.Sc.(Melit.) Wed, 01 Jan 2025 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/148117 2025-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/146213 Title: A practical checklist for return of results from genomic research in the European context Authors: Vears, Danya F.; Hallowell, Nina; Bentzen, Heidi Beate; Ellul, Bridget; Nøst, Therese Haugdahl; Kerasidou, Angeliki; Kerr, Shona M.; Mayrhofer, Michaela Th.; Mežinska, Signe; Ormondroyd, Elizabeth; Solberg, Berge; Sand, Birgitte Wirum; Budin-Ljøsne, Isabelle Abstract: An increasing number of European research projects return, or plan to return, individual genomic research results (IRR) to participants. While data access is a data subject’s right under the General Data Protection Regulation (GDPR), and many legal and ethical guidelines allow or require participants to receive personal data generated in research, the practice of returning results is not straightforward and raises several practical and ethical issues. Existing guidelines focusing on return of IRR are mostly projectspecific, only discuss which results to return, or were developed outside Europe. To address this gap, we analysed existing normative documents identified online using inductive content analysis. We used this analysis to develop a checklist of steps to assist European researchers considering whether to return IRR to participants. We then sought feedback on the checklist from an interdisciplinary panel of European experts (clinicians, clinical researchers, population-based researchers, biobank managers, ethicists, lawyers and policy makers) to refine the checklist. The checklist outlines seven major components researchers should consider when determining whether, and how, to return results to adult research participants: 1) Decide which results to return; 2) Develop a plan for return of results; 3) Obtain participant informed consent; 4) Collect and analyse data; 5) Confirm results; 6) Disclose research results; 7) Follow-up and monitor. Our checklist provides a clear outline of the steps European researchers can follow to develop ethical and sustainable result return pathways within their own research projects. Further legal analysis is required to ensure this checklist complies with relevant domestic laws. Sun, 01 Jan 2023 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/146213 2023-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/144349 Title: Determining the genotype frequency of the Diego blood group system in Malta Abstract: This study investigated the prevalence of key Diego (Di) blood group antigens (Dia , Dib , Wra , and Wrb ) in Maltese blood donors using a molecular genotyping approach, with the aim of improving rare blood group detection and enhancing transfusion compatibility. A polymerase chain reaction followed by restriction fragment length polymorphism (PCR-RFLP) was developed to genotype four alleles: DI*A (Dia ), DI*B (Dib ), DI02.03* (Wra ), and DI02.04* (Wrb ). High-quality genomic DNA was extracted from donor blood samples, and allele-specific primers were used to amplify target regions of the solute carrier family 4 member 1 SLC4A1 gene. Selected samples were validated through direct DNA sequencing to confirm assay specificity. Additionally, a standardised questionnaire was administered to record donor parental ancestry. The PCR-RFLP method yielded consistent and reproducible results. All individuals tested negative for the rare DI*A and DI02.03* alleles, indicating an absence of the Dia and Wra antigens. The common DI*B and DI02.04* alleles were detected in all samples, suggesting a Di(a-b+) and Wr(a-b+) phenotype across the cohort. Ancestry data showed that the majority of participants reported full Maltese lineage, and allele frequencies were consistent with those expected in European populations. In conclusion, this study provides the first molecular characterisation of the Di Blood Group System in the Maltese population. Although no rare alleles were identified, the developed PCR-RFLP platform proved reliable for Di genotyping and is suitable for integration into routine blood donor screening. These findings establish a reference point for future studies and support the implementation of DNA-based methods to enhance transfusion safety in increasingly diverse populations. Description: M.Sc.(Melit.) Wed, 01 Jan 2025 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/144349 2025-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/143492 Title: Investigating the role of lipopolysaccharide-stimulated monocytes in the development of immune tolerance in community-acquired pneumonia patients Abstract: Introduction: Pneumonia remains a leading cause of morbidity and mortality worldwide. Beyond antibiotic treatment, disease severity hinges on how monocytes balance immune defence and tolerance, a process which may paradoxically worsen outcomes. Background: Emerging evidence links monocyte “tolerance” in CAP to DNA methylation and metabolic shifts, yet why patients differ in cytokine output remains unclear. We hypothesized that transcriptional changes in monocytes underlie this heterogeneity. Methodology: The study included samples from a previously executed prospective observational investigation of CAP patients and control subjects (ELDERBIOME; NCT02928367). Specifically, RNA-seq data of monocytes purified from 75 patients, stimulated with LPS- or not. In addition, TNF-α levels in supernatants were used to stratify samples as LPS responders or non-responders. Read libraries were prepared using the KAPA RNA HyperPrep Kit with RiboErase. Sequencing was performed on the Illumina HiSeq 4000 platform. Bioinformatics included standard quality control metrics, graph-based read alignment, and subsequent DESeq2 modelling, and pathway/network enrichment. Results and Discussion: At padj ≤ 0.01, LPS reshaped expression of 7,033 genes (3,878 upregulated; 3,155 downregulated). Enrichment pinpointed heightened cytokine and interferon pathways, with type I interferons (IFNB1) strongly induced. TNF-α stratification revealed two distinct monocyte states: high responders amplified interferon signalling and HLA class II expression; low responders favoured antioxidant, ECM, and solute transport programmes. Conclusion: These findings uncover transcriptional blueprints explaining patientspecific monocyte behaviour in CAP. Understanding this immune polarity could guide strategies to rebalance hyperinflammation without compromising pathogen clearance. Description: M.Sc.(Melit.) Wed, 01 Jan 2025 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/143492 2025-01-01T00:00:00Z