Theses (MSc in Medical and Health Sciences)

Heavy metals and plastics pollutions in the environment are becoming more common due to their extensive usage in our everyday lives and improper waste management. Interaction between heavy metals with plastics has been shown to have negative effects to the ecosystem. The aim of this study was to investigate the influence of polyethylene (PE) microplastic (MP) and nanoplastic (NP) on the combined toxicity of copper (Cu) and cadmium (Cd) in microalgae. The effects of PEMP and NP on the toxicity of Cu and Cd were assessed based on the algal physiological responses such as photosynthetic pigment contents and oxidative stress response. Our results showed that after 10 days of exposure, Cu and Cd caused more growth inhibition to Raphidocelis subcapitata (CuIC50=32.32 mg/L, Cd IC50=23.25 mg/L) compared to Chlorella sp. TJ6-5 (CuIC50=34.77 mg/L, Cd IC50=36.45 mg/L). Combinations of Cu and Cd at various IC concentrations (IC10, IC25, IC50, IC90) displayed synergistic effects and caused higher observed toxicity to both algal species compared to the expected level of toxicity. Although PE MP and NP did not cause significant growth inhibition to both algae species at concentrations up to 2 g/L. However, presence of PE MP and NP did enhance the growth inhibition effect of Cu and Cd (at IC50) on both algal strains with higher lipid peroxidation and reactive oxygen species (ROS) production. In addition, our results showed the combined exposure to mixture of PE MP and NP and Cu and Cd can compromise the cellular antioxidant defence capacity, potentially leading to increased susceptibility to oxidative damage and cellular death. In conclusion, the presence of PE MP/NP enhance the toxicity of Cu and Cd to freshwater microalgae particularly in R. subcapitata and Chlorella sp., with species-specific responses and varying degrees of synergistic effects.

Metal-organic frameworks (MOFs) are hybrid crystalline porous materials comprising metal ions linked with organic building units via coordination bonds. Their high surface area, large porosity, and tunable structures make them ideal for medical, environmental, and industrial applications. However, MOFs are often synthesised using aromatic organic linkers derived from non-renewable petrochemicals, which are non-biodegradable and less biocompatible. Additionally, the common solvothermal synthesis method is time-consuming and yields lower output. To address these challenges, this study developed aliphatic zinc-based MOFs (ZnMOFs) using a microwave-assisted method. This approach significantly reduced reaction time while improving yield without compromising structural integrity. The ZnMOFs were characterised for their physicochemical properties, morphology, and thermal stability, demonstrating their suitability for biomedical applications. Doxorubicin (DOX), an anticancer agent, was loaded into the ZnMOFs to assess their drug delivery potential. The ZnMOFs achieved efficient drug encapsulation and exhibited controlled DOX release in acidic conditions (pH 5.6), mimicking the tumor microenvironment. Biological evaluations highlighted the biocompatibility and therapeutic potential of the ZnMOFs. Cytotoxicity assays revealed that ZnTDA MOF and ZnHDA MOF exhibited low toxicity towards both MCF-7 cancer cells (20-25% cytotoxicity) and HEK293 normal cells (IC50 = 1785-2374 μg/mL) while maintaining effective drug delivery with up to 40% cytotoxicity when loaded with DOX. In contrast, DOX-loaded ZnAdA MOF, DOX-loaded ZnDDA MOF, and DOX-loaded ZnAzA MOF even though showing lower cellular uptake but significantly higher cytotoxicity (up to 90%) against MCF-7 cells, suggesting a synergistic effect between the MOFs and DOX. These MOFs also demonstrated minimal toxicity towards HEK293 cells (IC50 = 117.4-1785 μg/mL), indicating their safety for normal cells. Overall, the synthesised aliphatic ZnMOFs via a microwave- assisted method are efficient, biocompatible, and effective in targeted cancer treatment. Their ability to encapsulate and release drugs in a controlled manner while reducing toxicity highlights their potential as safer alternatives to conventional MOF-based drug delivery systems.

Diabetes is a highly prevalent metabolic disorder that stands as an independent risk factor for respiratory infection which was identified as the second leading cause of premature mortality in Malaysia in 2018. The gut microbiome is fundamental for physiological metabolic and immunological processes both locally and at distant sites for instance the pulmonary termed the gut-lung axis. Such inter-organ crosstalk occurs mainly via the translocation of metabolites. The implication of the gut-lung axis becomes evident following the identification of perturbated gut microbial composition, termed gut dysbiosis, among those with diabetes who are more susceptible to respiratory infections. However, such an association in the Malaysian diabetic population is underexplored. In this study, we aim to examine the carriage rate of upper respiratory tract pathobionts, and to identify the gut microbial and metabolome signatures related to diabetes. A total of 31 Type 2 diabetics and 14 controls were recruited from Hospital Putrajaya and public community. Each subject provided nasopharyngeal (NP), urine and stool samples. DNA was extracted from NP and stool samples and analysed using 16S rRNA sequencing targeting V3-V4 hypervariable regions. Urine samples were analysed using 1H-NMR. In the gut microbiome of diabetics, beneficial short chain fatty acid producing bacteria Dorea sp, Diallister sp. and Romboutsia illealis were reduced. Significantly higher levels of urinary D-sorbitol and taurine were reported in diabetics. A higher prevalence of opportunistic respiratory pathogens S. agalactiae and M. catarrhalis were observed among diabetics. These changes in gut microbiome and urine metabolome are linked to impaired general immunity, which may contribute to the observed enrichment of respiratory pathogens and potentially raising susceptibility to respiratory infections. These results would shed light on developing novel and targeted therapies for diabetes and associated respiratory infections.

Per- and polyfluoroalkyl substances (PFASs) are extensively utilised in various industrial and commercial application due to their exceptional thermal stability, low surface tension, and water- and oil-repellent properties, such as the production of nonstick coatings ion cookware, bakeware, disposable food packaging, stain- and water-resistant textiles. Among these, perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) are the most extensively studied and well-known PFAS. Their bioaccumulation and persistence pose adverse effects on human health, primarily lungs, liver and kidneys. Despite their known effects, the specific mechanisms underlying PFAS-induced respiratory toxicity remained poorly understood. This study investigated the molecular mechanisms of lung toxicity induced by PFOA and PFOS in human normal bronchial epithelial BEAS-2B cells and normal lung MRC-5 fibroblasts. Our findings demonstrated that both PFOA and PFOS induced apoptosis and altered cell cycle distribution pattern in human lung cells. KEGG pathway analysis identified IL-17 and TNF signalling pathways as the potential modulated toxicity pathways responsible for PFOA and PFOS-induced apoptosis and altered cell cycle distribution pattern. Further analysis revealed significant upregulation of transcription factors (FOSL1 and CREB5) and proinflammatory cytokines (IL-6 and CXCL8), in response to PFOA or PFOS exposure. Functional validation studies demonstrated that 666-15 (selective CREB inhibitor) effectively ameliorated the overexpression of IL-6 and CXCL8 induced by PFOA and PFOS. While T-5224 (selective FOSL1 inhibitor) only ameliorated the overexpression of IL-6 and CXCL8 by PFOA, but not PFOS. Taken together, PFOA or PFOS may play a potential role in mediating the release of pro-inflammatory cytokines and lung inflammation, primarily through TNF and IL-17 signalling pathways, with potential involvement of other pathways such as NF-κB signalling pathway.

Pancreatic cancer is a lethal form of malignancy with a high mortality rate. The poor survival rate is likely due to its aggressive nature and its early detection challenges. The current confirmative diagnosis of pancreatic cancer is through manual examination of tissue biopsy by pathologists under a microscope. This method is time consuming and often results in late or deferred treatment. The lack of pathologists specialised in hepatobiliary in Malaysia contributes to further delay of treatment especially in rural areas. This study confers a classification of pancreatic cancer cells extracted from whole slides images to aid pathologists to reach a diagnosis faster. A total of 21 pancreatic fine needle aspirate Papanicolaou (PAP) smears and cell blocks (CB) was obtained from the Pathology Department, Hospital Selayang, digitised using a whole slide scanner and segmented into single cell images for annotation. Annotated single cell images of cancerous and normal cell types were used to train an artificial intelligence (AI)-model that is able to differentiate pancreatic cancer cells from non-cancerous normal cells. From 21 whole slide images (WSIs), 4149 single cell images were extracted for establishment of cell database (3210 cancerous pancreatic cells, 939 normal pancreatic cells). DenseNet21 model was used for the training of pancreatic cancer detection. A total of 3320 single cell images was used for the training and validation, while the remaining 829 cell images were used for the testing of the developed PAP and CB models. The models were able to detect and classify the test dataset up to 97.8% accuracy for CB model and 91.04% for PAP model. This automated pancreatic cancer algorithm can be implemented together with an online digital pathology platform for the uses in hospitals across Malaysia. This can hasten diagnosis and aid rural areas with a scarce number of specialised pathologists to assist in the diagnosis of pancreatic cancer.