Evaluation of quality of life in patients treated for colorectal cancer at the University Hospital Trnava

Introduction: The aim of the study was to evaluate quality of life (QoL) in patients with colorectal cancer (CRC) during complex treatment using the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 and QLQ-CR29 questionnaires and to implement routine QoL assessment into our practice. Methods: 30 patients diagnosed with CRC at the Department of Surgery, Faculty Hospital Trnava, Slovakia were included in the study between May 2014 and April 2015. QoL was assessed using EORTC QLQ-C30 and QLQ-CR29 questionnaires before surgery and 1 month after surgery. Data are presented as means, and a paired t-test and independent t-test were used for statistical analysis. Results: A significant correlation between the type of treatment and QoL was identified in the cohort. A trend to lower QoL was observed in patients with completed neoadjuvant chemoradiotherapy (CRT) and after surgery with stoma formation. The QoL was also affected by the age and gender of the patients. Conclusion: QoL assessment provides important outcomes reflecting the consequences of particular therapeutic modality in patients with CRC. The worse effect of neoadjuvant CRT and stoma formation was shown in our study in comparison to radical resection with adjuvant chemotherapy

Drivers and epidemiological patterns of West Nile virus in Serbia

Background: West Nile virus (WNV) is an emerging mosquito-borne pathogen in Serbia, where it has been detected as a cause of infection in humans since 2012. We analyzed and modelled WNV transmission patterns in the country between 2012 and 2023. Methods: We applied a previously developed modelling approach to quantify epidemiological parameters of interest and to identify the most important environmental drivers of the force of infection (FOI) by means of statistical analysis in the human population in the country. Results: During the study period, 1,387 human cases were recorded, with substantial heterogeneity across years. We found that spring temperature is of paramount importance for WNV transmission, as FOI magnitude and peak timing are positively associated with it. Furthermore, FOI is also estimated to be greater in regions with a larger fraction of older adult people, who are at higher risk to develop severe infections. Conclusion: Our results highlight that temperature plays a key role in shaping WNV outbreak magnitude in Serbia, confirming the association between spring climatic conditions and WNV human transmission risk and thus pointing out the importance of this factor as a potential early warning predictor for timely application of preventive and control measure

Demographic and socioeconomic factors associated with cervical cancer screening among women in Serbia

ObjectivesEffective reduction of cervical cancer incidence and mortality requires strategic measures encompassing the implementation of a cost-effective screening technology. Serbia has made significant strides, introducing organized cervical cancer screening in 2012. However, various impediments to screening implementation persist. The aim of the study was to estimate the socioeconomic factors associated with cervical cancer screening among women in Serbia.MethodsData from 2019 National Health Survey of the population of Serbia were used in this study. The study is cross sectional survey on a representative sample of the population of Serbia. Present total number of participants analyzed in survey 6,747.ResultsIn Serbia, 67.2% of women have done a Pap test at any time during their lives, of which 46.1% of women have undergone cervical cancer screening in the past 3 years. About a quarter of women have never undergone a Pap test in their life (24.3%). The probability of never having a Pap test have: the youngest age group (15–24 years) is 1.3 times more likely than the oldest age group (OR = 1.31), unmarried women 0.3 times more often than married women (OR = 0.37), respondents with basic education 0.9 times more often than married women (OR = 0.98), the women of lower socioeconomic status 0.5 times more often than respondents of high socioeconomic status (OR = 0.56).ConclusionEnhancement of the existing CCS would be the appropriate public health approach to decrease the incidence and mortality of cervical cancer in the Republic of Serbia

EpiCRISPR targeted methylation of Arx gene initiates transient switch of mouse pancreatic alpha to insulin-producing cells

Introduction: Beta cell dysfunction by loss of beta cell identity, dedifferentiation, and the presence of polyhormonal cells are main characteristics of diabetes. The straightforward strategy for curing diabetes implies reestablishment of pancreatic beta cell function by beta cell replacement therapy. Aristaless-related homeobox (Arx) gene encodes protein which plays an important role in the development of pancreatic alpha cells and is a main target for changing alpha cell identity. Results: In this study we used CRISPR/dCas9-based epigenetic tools for targeted hypermethylation of Arx gene promoter and its subsequent suppression in mouse pancreatic αTC1-6 cell line. Bisulfite sequencing and methylation profiling revealed that the dCas9-Dnmt3a3L-KRAB single chain fusion constructs (EpiCRISPR) was the most efficient. Epigenetic silencing of Arx expression was accompanied by an increase in transcription of the insulin gene (Ins2) mRNA on 5th and 7th post-transfection day, quantified by both RT-qPCR and RNA-seq. Insulin production and secretion was determined by immunocytochemistry and ELISA assay, respectively. Eventually, we were able to induce switch of approximately 1% of transiently transfected cells which were able to produce 35% more insulin than Mock transfected alpha cells. Conclusion: In conclusion, we successfully triggered a direct, transient switch of pancreatic alpha to insulin-producing cells opening a future research on promising therapeutic avenue for diabetes management. 1 Introductio

Methodological approach towards a Gap Assessment of the Serbian microbiology system in the function of surveillance in line with EU standards and acquis

Introduction. Italian and Serbian Health authorities performed an in-depth Gap Assessment of the Serbian microbiology system in the function of communicable disease surveillance using a methodology adapted to context and information needs. Methods. There were two study phases: a capacity based survey and an equipment mapping survey. Invited participants included national health authorities, heads of national reference laboratories and of public/private diagnostic laboratories in Serbia. Findings were analysed preliminarily and identified gaps were discussed, prioritized and validated through two ad hoc workshops involving all concerned institutions. Results. The Gap Assessment was performed between September and December 2017.The overall response rate was 69% for phase one and 74% for phase two. Identified gaps were assessed as highly relevant during the project workshops. Discussion. Gaps and priorities were highlighted, validated, and studied with a suitable level of detail to develop a concrete action-plan. The same methodological approach

RISK ENVIRONMENTAL FACTORS FOR CHILDHOOD ASTHMA

Besides personal characteristics inherited or acquired, exposure to outdoor pollutant and risk environmental factors during fetal and postnatal period can play an important role for development of childhood asthma. Differentiation of allergen specific T cells into dominant Th2 phenotype can be caused by mom-to-be or a young baby exposure to high concentrations of allergens, irritants, tobacco smoke or some other pollutants. One of the possible premises was given by the hygiene hypotheses. It is based on reciprocal relation between the incidence of infective diseases in early childhood and, as a consequence, occurrence of asthma and other infective diseases later on. Epidemiological, biological and genetic studies have given proofs to enlarge the scale of this hypothesis. According to them, there is a possibility that the loss of normal immune balance arises from extremely clean way of life, where the number of microbes is very reduced. In such circumstances the immune system reacts to every kind of “danger” by allergic responses and allergic diseases, including asthma

Unveiling the Comorbidities of Chronic Diseases in Serbia Using ML Algorithms and Kohonen Self-Organizing Maps for Personalized Healthcare Frameworks

In previous years, significant attempts have been made to enhance computer-aided diagnosis and prediction applications. This paper presents the results obtained using different machine learning (ML) algorithms and a special type of a neural network map to uncover previously unknown comorbidities associated with chronic diseases, allowing for fast, accurate, and precise predictions. Furthermore, we are presenting a comparative study on different artificial intelligence (AI) tools like the Kohonen self-organizing map (SOM) neural network, random forest, and decision tree for predicting 17 different chronic non-communicable diseases such as asthma, chronic lung diseases, myocardial infarction, coronary heart disease, hypertension, stroke, arthrosis, lower back diseases, cervical spine diseases, diabetes mellitus, allergies, liver cirrhosis, urinary tract diseases, kidney diseases, depression, high cholesterol, and cancer. The research was developed as an observational cross-sectional study through the support of the European Union project, with the data collected from the largest Institute of Public Health “Dr. Milan Jovanovic Batut” in Serbia. The study found that hypertension is the most prevalent disease in Sumadija and western Serbia region, affecting 9.8% of the population, and it is particularly prominent in the age group of 65 to 74 years, with a prevalence rate of 33.2%. The use of Random Forest algorithms can also aid in identifying comorbidities associated with hypertension, with the highest number of comorbidities established as 11. These findings highlight the potential for ML algorithms to provide accurate and personalized diagnoses, identify risk factors and interventions, and ultimately improve patient outcomes while reducing healthcare costs. Moreover, they will be utilized to develop targeted public health interventions and policies for future healthcare frameworks to reduce the burden of chronic diseases in Serbia

Ensemble Model for Predicting Chronic Non-Communicable Diseases using Latin Square Extraction and Fuzzy-Artificial Neural Networks from 2013 to 2019

Background: The presented study tracks the increase or decrease in the prevalence of seventeen different chronic non-communicable diseases in Serbia. This analysis considers factors such as region, age, and gender and is based on data from two national cross-sectional studies conducted in 2013 and 2019. The research aims to accurately identify the regions with the highest percentage of affected individuals, as well as their respective age and gender groups. The ultimate goal is to facilitate organized, free preventive screenings for these population categories within a very short time-frame in the future. Materials and methods: The study analyzed two cross-sectional studies conducted between 2013 and 2019, using data obtained from the Institute of Public Health of Serbia. Both studies involved a total of 27801 participants. The study compared the performance of Decision Tree and Support Vector Regressor models with artificial neural network (ANN) models that employed two encoding functions. The new methodology for the ANN-L36 model was based on artificial neural networks constructed using a Latin square (L36) design, incorporating Taguchi's robust design optimization. Results: The results of the analysis from three different models have shown that cardiovascular diseases are the most prevalent illnesses among the population in Serbia, with hypertension as the leading condition in all regions, particularly among individuals aged 64 to 75 years, and more prevalent among females. In 2019, there was a decrease in the percentage of the leading disease, hypertension, compared to 2013, with a decrease from 34.0% to 32.2%. The ANN-L36 model with Fuzzy encoding function demonstrated the highest precision, achieving the smallest relative error of 0.1%. Conclusion: To date, no studies have been conducted at the national level in Serbia to comprehensively track and identify chronic diseases in the manner proposed by this study. The model presented in this research will be implemented in practice and is set to significantly contribute to the future healthcare framework in Serbia, shaping and advancing the approach towards addressing these conditions. Furthermore, experimental evidence has shown that Taguchi's optimization approach yields the best results for identifying various chronic non-communicable diseases.</p

Key factors determining indoor air PM10 concentrations in naturally ventilated primary schools in Belgrade, Serbia

Indoor air quality (IAQ) is rated as a serious public health issue. Knowing children are accounted as more vulnerable to environmental health hazards, data are needed on air quality in schools