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Celiac disease (CD) is a chronic inflammatory disease in the small intestine triggered by gluten uptake that occurs in genetically susceptible individuals. HLA-DQ2 protein encoded by HLA-DQA1*05 and DQB1*02 alleles is found in 90-95% of CD patients. All of the remaining patients carry HLA-DQ8 protein encoded by HLA-DQA1*03 and DQB1*03:02 alleles. Specific HLA-DQ genotypes define different risk for CD incidence. Presence of susceptible HLA-DQ genotypes does not predict certain disease development, but their absence makes CD very unlikely, close to 100%. Here we presented for the first time the distribution of HLA-DQ genotypes in the group of pediatric celiac patients from the University Children’s Hospital, Belgrade, Serbia and estimated risk for CD development that these genotypes confer. Seventy three celiac disease patients and 62 healthy individuals underwent genotyping for DQA1, DQB alleles and DRB1 allele. 94.5% of patients carried alleles that encode DQ2 protein variant and 2.7% carried alleles that encode DQ8 protein variant. Two patients carried single DQB1*02 allele. No patients were negative for all the alleles predisposing to CD. The highest HLA-DQ genotype risk for CD development was found in group of patients homozygous for DQ2.5 haplotype, followed by the group of heterozygous carriers of DQ2.5 haplotype in combination with DQB1*02 allele within the other haplotype. The lowest risk was observed in carriers of a single copy of DQB1*02 or DQA1*05 allele or other non-predisposing alleles. HLA genotyping, more informative than serological testing commonly used, proved to be a useful diagnostic tool for excluding CD development.

The use of non-vitamin K antagonist oral anticoagulants (NOACs) has brought a significant progress in the management of cardiovascular diseases, considered clinically superior to vitamin K antagonists (VKAs) particularly in the prevention and treatment of thromboembolic events. In addition, numerous advantages such as fixed dosing, lack of laboratory monitoring, and fewer food and drug-to-drug interactions make the use of NOACs superior to VKAs. While NOACs are synthetic drugs prescribed for specific conditions, nattokinase (NK) is a natural enzyme derived from food that has potential health benefits. Various experimental and clinical studies reported the positive effects of NK on the circulatory system, including the thinning of blood and the dissolution of blood clots. This enzyme showed not only fibrinolytic activity due to its ability to degrade fibrin, but also an affinity as a substrate for plasmin. Recent studies have shown that NK has additional cardioprotective effects, such as antihypertensive and anti-atherosclerotic effects. In this narrative review, we presented the cardioprotective properties of two different approaches that go beyond anticoagulation: NOACs and NK. By combining evidence from basic research with clinical findings, we aim to elucidate the comparative cardioprotective efficacy of these interventions and highlight their respective roles in modern cardiovascular care.

The effectiveness of chemotherapy in cancer cell regression is often limited by drug resistance, toxicity, and neoplasia heterogeneity. However, due to the significant complexities entailed by the many cancer growth processes, predicting the impact of interference and symmetry-breaking mechanisms is a difficult problem. To quantify and understand more about cancer drug pharmacodynamics, we combine in vitro with in silico cancer models. The anti-proliferative action of selected cytostatics is interrogated on human colorectal and breast adenocarcinoma cells, while an agent-based computational model is employed to reproduce experiments and shed light on the main therapeutic mechanisms of each chemotherapeutic agent. Multiple drug administration scenarios on each cancer cell line are simulated by varying the drug concentration, while a Bayesian-based method for model parameter optimisation is employed. Our proposed procedure of combining in vitro cancer drug screening with an in silico agent-based model successfully reproduces the impact of chemotherapeutic drugs in cancer growth behaviour, while the mechanisms of action of each drug are characterised through model-derived probabilities of cell apoptosis and division. We suggest that our approach could form the basis for the prospective generation of experimentally-derived and model-optimised pharmacological variables towards personalised cancer therapy.