We have studied the kinetics of the complex formation of gold(III) complexes, [Au(en)Cl2]+ (dichlorido( ethylendiamine)aurate(III)-ion) [Au(dach)Cl2] (dichloride(1,2-diaminocyclohexane)aurate(III)-ion) and [Au(bipy)Cl2]+ (dichlorido(2,2'-bipyridyl)aurate(III)-ion) with guanosine5'-monophosphate (5'-GMP). It was shown that 5'-GMP have a high affinity for gold(III) complex, which may have important biological implications, since the interactions of Au(III) with DNA are thought to be responsible for the anti-tumor activity. The [Au(bipy)Cl2]+ complex is more reactive than [Au(en)Cl2]+ or [Au(dach)Cl2]+. The activation parameters for all studied reactions suggest an associative substitution mechanism. The cytotoxicity of gold(III) complexes was tested on A549 human lung carcinoma epithelial cell line and was evaluated by cytotoxic (MTT and LDH test) and apoptotic assays. The results showed that all tested gold(III) complexes displayed cytotoxic effect on A549 cells. Among the tested gold (III) complexes, AuBIPY showed the best cytotoxic effects.

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COVID-19 represents one of the greatest challenges in modern history. Its impact is most noticeable in the health care system, mostly due to the accelerated and increased influx of patients with a more severe clinical picture. These facts are increasing the pressure on health systems. For this reason, the aim is to automate the process of diagnosis and treatment. The research presented in this article conducted an examination of the possibility of classifying the clinical picture of a patient using X-ray images and convolutional neural networks. The research was conducted on the dataset of 185 images that consists of four classes. Due to a lower amount of images, a data augmentation procedure was performed. In order to define the CNN architecture with highest classification performances, multiple CNNs were designed. Results show that the best classification performances can be achieved if ResNet152 is used. This CNN has achieved AUCmacro¯ and AUCmicro¯ up to 0.94, suggesting the possibility of applying CNN to the classification of the clinical picture of COVID-19 patients using an X-ray image of the lungs. When higher layers are frozen during the training procedure, higher AUCmacro¯ and AUCmicro¯ values are achieved. If ResNet152 is utilized, AUCmacro¯ and AUCmicro¯ values up to 0.96 are achieved if all layers except the last 12 are frozen during the training procedure.

Guillain-Barré syndrome (GBS) is an acute auto-immune polyradiculoneuropathy. A huge variety of GBS incidence and mortality rates has been noted across the world. The objective of the present multi-centric study was to assess the incidence and mortality rates of GBS during a 10-year period in Serbia. We collected data of adult GBS patients who were hospitalized from 2009 to 2018 in all five tertiary healthcare centers in Serbia. The incidence rates per 100 000 inhabitants with 95% confidence intervals (CI) were calculated and further corrected for the estimated number of patients hospitalized in secondary centers. Mortality rates were also assessed. GBS was considered severe if patients were not able to walk at least 10 m without assistance. Six hundred and forty GBS patients were registered in tertiary centers in a 10-year period. The proportion of severe cases was 75% at nadir, and 52% on discharge. GBS incidence rate in Serbia was 1.1 per 100 000 inhabitants, and estimated incidence if patients from secondary centers included 1.2 per 100 000. Peak incidence was observed during the sixth decade of life. During the acute phase, 5.6% of GBS patients died, while overall 9.7% of them died during 6-month period from disease onset. This study contributes to our knowledge about GBS epidemiology. Results will allow us to improve the diagnosis and treatment of GBS patients in Serbia.