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Ms Celine Ann Grech
Department of Anatomy, Faculty of Medicine and Surgery

Intrahepatic cholestasis of pregnancy (ICP) and preeclampsia (PE) are two major pregnancy complications that adversely affect maternal and perinatal outcomes. While ICP is recognised as a risk factor for PE, the shared underlying pathophysiology remains incompletely understood. In this study, we aimed to identify shared differentially expressed genes (DEGs) and dysregulated biological pathways between ICP and PE to elucidate common molecular mechanisms. Placental microarray datasets from ICP and PE were retrieved from the NCBI Gene Expression Omnibus and analysed using limma, Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) network analyses. A total of 291 shared DEGs were identified, with FIBCD1 and SH2D6 among the most significantly dysregulated genes. Enrichment analysis of shared DEGs in placental tissues identified pathways involving metabolic, immune, and signalling cascades. Metabolic pathways, such as negative regulation of catabolic process, response to nutrient levels, and sphingolipid catabolism, were identified, alongside immune processes including response to bacteria, neutrophil migration, and OAS antiviral response. Furthermore, regulatory pathways like G-protein-coupled receptor (GPCR) downstream signalling, transient receptor potential (TRP) channels, TP53 regulation of gene transcription, and the ADP-ribosylation factor 6 (ARF6) pathway were also enriched. These findings suggest metabolic, immune, and hormonal dysregulation contributing to placental dysfunction in both conditions. The identified DEGs provide insights into the shared aetiology of ICP and PE, supporting a better understanding of the integrated regulatory pathways. 

Ms Lara Sammut
Department of Anatomy, Faculty of Medicine and Surgery

Threatened miscarriage remains one of the most challenging presentations in early pregnancy, with significant implications for clinical decision-making and patient anxiety. A three-phase research study was undertaken to clarify prevalence, identify robust predictive markers, and develop an early risk-stratification algorithm. The first phase involved a retrospective cohort analysis of 711 women presenting with first-trimester bleeding at Malta’s national state hospital, identifying a TM progression rate to live birth of 33.9%, increased miscarriage risk with maternal age ≥35 years, and reduced gestational age and birthweight among surviving neonates. The second phase comprised a scoping review of 128 studies evaluating ultrasound and biochemical predictors of early pregnancy failure. Key markers consistently associated with adverse outcomes included foetal heart rate deviations, yolk sac abnormalities, intrauterine haematoma, progesterone, β-chg., and emerging angiogenic ratios. Evidence heterogeneity highlighted the need for a structured, multi-marker predictive approach. The final phase involved a prospective case-control study of 118 TM cases and 59 controls, integrating ultrasound, biochemical, demographic, and clinical variables into a predictive algorithm built using multivariate logistic regression and an Artificial Intelligence method based on Random Forest (RF) classification. Logistic regression achieved strong performance (AUC 0.85), while the RF model demonstrated superior accuracy (AUC 0.968; accuracy 93.1%), effectively modelling complex, non-linear interactions and enhancing risk discrimination. Together, these three phases deliver a locally validated, AI-enabled predictive tool that supports earlier, more personalised counselling and management for women presenting with first-trimester bleeding.

Ms Francesca Borg Carbott  |  Co-researchers: Ms Charlene Portelli, Dr David Agius, Dr Ritienne Attard, Dr Adrian Mifsud, Mr Isaac Bertuello, Ms Gabriella Sciriha, Prof. Julian Mamo, Dr Karen Cassar, Prof. Rosienne Farrugia, Prof. Francis Carbonaro and Prof. Jean Paul Ebejer
Department of Applied Biomedical Science, Faculty of Health Sciences

Glaucoma is a leading cause of irreversible visual impairment and blindness worldwide, characterised by silent, progressive optic nerve degeneration. Pseudoexfoliation syndrome (XFS) is the most common, identifiable cause of secondary open-angle glaucoma (OAG). Early detection and targeted intervention are critical to reduce the global burden of glaucoma. In this study, we evaluated the clinical screening utility of a polygenic risk score (PRS) developed by Han et al. (2023) for primary open-angle glaucoma (POAG) in predicting XFS with or without glaucoma (XFS/XFG) in the Maltese population. Additionally, we developed and assessed an in-house PRS model tailored for XFS/XFG. Whole genome sequencing (WGS) was performed on 47 unrelated research subjects from two independent XFS/XFG collections: the Malta Glaucoma Project (MGP; n=25) and the Malta Eye Study (MES; n=22). Population controls (n=395) were obtained from the Maltese Acute Myocardial Infarction Study. The POAG PRS was evaluated using all cases and controls. The in-house PRS was trained on the MGP cases and tested on the MES cases. Individuals in the top 10% of both the POAG PRS (OR=2.7, 95% CI: 1.1–5.9, p=0.039) and the in-house PRS (mean OR=4.0; range: 3.6–4.8, mean p=0.036; range: 0.025–0.047) had increased risk of XFS/XFG. However, the in-house PRS showed markedly better screening potential (mean DR5=35.6%, OAPR=1:4.4–1:8.8, vs. DR5=17%, OAPR=1:15, assuming 2% disease prevalence). These findings highlight the value of population-specific PRS models for XFS/XFG risk prediction and clinical screening.

In摹. Federico Cilia
Department of Physics, Faculty of Science

Microwave ablation (MWA) is a minimally invasive treatment for tumours in organs like the liver, kidneys, and lungs. Despite its clinical adoption, MWA faces challenges due to limited knowledge of tissue dielectric properties and their changes during ablation. These properties are critical for predicting ablation zone size and shape, but current data, often derived from ex vivo tissues, fail to account for perfusion and temperature effects. This lack of accurate, dynamic data limits treatment planning and efficacy, increasing reliance on clinician judgment.

This project addresses these limitations by thoroughly characterising tissue dielectric properties under perfused and heated conditions. This will be achieved through a novel dual-mode ablation technique that records real-time permittivity measurements during treatment. The data will assist in developing a thermosensitive phantom that accurately reflects the dielectric properties of tissues during ablation.

By combining dual-mode ablation dielectric measurement techniques, realistic experimental phantoms, and innovative antenna design, ABLAZE aims to improve the safety, precision, and effectiveness of MWA and reduce the need for on-the-fly clinical decisions.