The aim of this study was to investigate the therapeutic potential of resveratrol in combination with cisplatin on the inhibition of tumour angiogenesis, growth, and macrophage polarization in mice bearing the solid form of an Ehrlich ascites tumour (EAT) that were exposed to whole-body hyperthermia treatment. In addition, we investigated whether a multimodal approach with hyperthermia and resveratrol could abolish cisplatin resistance in tumour cells through the modulation of histone deacetylase (HDAC) activity and levels of heat shock proteins (HSP70/HSP90) and contribute to the direct toxicity of cisplatin on tumour cells. The tumour was induced by injecting 1 × 106 EAT cells subcutaneously (sc) into the thighs of Balb/c mice. The mice were treated with resveratrol per os for five consecutive days beginning on day 2 after tumour injection and/or by injecting cisplatin intraperitoneally (ip) at a dose of 2.5 mg/kg on days 10 and 12 and at a dose of 5 mg/kg on day 15. Immediately thereafter, the mice were exposed to systemic hyperthermia for 15 min at a temperature of 41 °C. The obtained results showed that the administration of resveratrol did not significantly contribute to the antitumour effect of cisplatin and hyperthermia, but it partially contributed to the immunomodulatory effect and to the reduction of cisplatin toxicity and to a slight increase in animal survival. This treatment schedule did not affect microvessel density, but it inhibited tumour growth and modulated macrophage polarization to the M1 phenotype. Furthermore, it abolished the resistance of tumour cells to cisplatin by modulating HDAC activity and the concentration of HSP70 and HSP90 chaperones, contributing to the increased lifespan of mice. However, the precise mechanism of the interaction between resveratrol, cisplatin, and hyperthermia needs to be investigated further.

At the beginning of 2020, the Sarajevo-based publishing house El-Kalem, released a biography of Derviš M. Korkut, a Bosniak hero, to whom Yad Vashem posthumously awarded Righteous among the Nations on December 14, 1994. Winston Churchill's words, with which the author begins the biography—that the Balkans produce more history than they can handle—best describe the difficult times in which Korkut lived. For Korkut and his fellow Bosnians, these difficult times lasted from the beginning of the 20th century to its very end. The book is based on exhaustive archival research and reconstructs Korkut’s life very precisely, while the concise overview of the historical circumstances of the 20th century in the Balkans, and in Bosnia and Herzegovina, allows a better understanding of his actions. His defense of his Jewish neighbors began early when the Minister of Interior of the newly established Kingdom of Serbs, Croats, and Slovenes, Milorad Drašković, initiated a procedure for the disenfranchisement of Yugoslav Jews. Korkut took part in the campaign against Drašković’s policies, publicly condemned such a policy, and gave a speech in the town of Derventa, in favor of the Jews When, at the beginning of 1942, Nazi General Johann Hans Fortner came to the National Museum, demanding the handover of the Haggadah—a 15th-century Jewish manuscript brought to Bosnia and Herzegovina by Sephardic Jews who settled in Sarajevo, then part of the Ottoman Empire—Korkut managed to save the Haggadah, risking his own life in doing so (p. 40). Shortly after rescuing the Haggadah, a friend asked Korkut to help a Jewish girl, Donkica Papo (later Mira Baković), whose parents had already been sent to an Ustasha camp. After spending several months hiding in Korkut’s house, he managed to obtain forged documents for her and save her. In 1994, while Bosnia and Herzegovina was ravaged once again by the war, Mira Baković wrote to Yad Vashem, explaining how Derviš and his wife Servet Korkut had saved both her life and the Haggadah. Yad Vashem posthumously awarded him “Righteous Among the Nations” on December 14, 1994 at the Israeli Embassy in Paris (p. 63). This poignant, well-written biography shows not only a life of a truly remarkable man, but also how difficult times throughout the 20th century, reflected on the people in Bosnia and Herzegovina and how they tried to respond to them by preserving the unique Bosnian multi-ethnic, multi-confessional, and multicultural community. The story of Derviš M.Korkut’s life, marked by courage, perseverance, and resistance needs to be given the place in collective memory that it deserves, a task this book achieves. Written in English and thus available to a wider readership, it not only pays tribute to Derviš M. Korkut, but also sheds light on the Sarajevo he sought to preserve at the risk of his life.

Progress towards effective treatment of epileptic seizures has seen much improvement in the past decade. In particular, the emergence of phenomenological models of epileptic seizures specifically designed to capture the electrical seizure dynamics in the Epileptor model is inspiring new approaches to predicting and controlling seizures. These new models present in various forms and contain important but unmeasurable variables that control the occurrence of seizures. These models have been used mostly as nodes in large networks to study the complex brain behaviour of seizures. In order to use this model for the purposes of seizure forecasting or to control seizures through deep brain stimulation, the states of the model will need to be estimated. Although devices such as EEG electrodes can be related to some of the states of the model, most remain unmeasured and would require an observer (as defined in control theory) for their estimation. Additionally, we would like to consider the case for large nodes of systems where the number of electrodes is far smaller than the number of nodes being estimated. In this paper, we provide methods towards obtaining the full states of these phenomenological models using nonlinear observers. In particular, we explore the effectiveness of the Extended Kalman Filter for small networks of nodes of a smoothed sixth order Epileptor model. We show that observer design is possible for this family of systems and identify the difficulties in doing so.Clinical relevance—The methods presented here can be applied with an individual epileptic patient’s EEG to reveal previously hidden biomarkers of epilepsy for seizure forecasting.

The paper presents a PyDigitizer application designed to extract numerical coordinates of existing curves from image format. The application is created in the Python programming language and offers the possibility of manual extraction of curve coordinates, intersection of curves with user-specified abscissa or ordinate, generation of polynomial regression equations of curves. All generated information (coordinates, intersection points, regression curves) can be exported to Microsoft Excel. Also, point coordinates of Excel curves can be loaded into PyDigitizer to obtain polynomial regression curves or intersections.

During the operation of each machine, the deformation and stress state of its supporting structure is directly related to the load. The load intensity ranges from the minimum to the maximum value and is a function of nominal force, torque, and kinematic-dynamic values of moving and executive assemblies during the machine operation process. The intensity of deformations is also a function of the shape and type of the supporting structure. However, although the supporting structure is reliable, which refers to its integrity, the production of a quality workpiece (product) does not have to be reliable. Therefore, it is important that the deformation states of the supporting structure be in the appropriate tolerance field, regardless of the intensity of the load. If the intensity of deformations is outside a certain field, it will directly affect the quality of the workpiece that is made on the subject machine. It is known that load-bearing structures can be of open and closed types, load-bearing structures of closed type are used for higher loads and larger workpiece dimensions. By installing sensors on the elements of the supporting structure with accompanying measuring chains in real-time, the deformation state of certain elements or places on the supporting structure can be monitored, based on which the reliable quality of the workpiece can be influenced.

Although miRNA-27a has been identified as a promising candidate for miRNA mimic therapy of obesity, its application is limited due to enzymatic degradation and low membrane permeation. To overcome these problems, we developed cationic nanostructured lipid carriers (cNLCs) using high-pressure homogenization and used them as non-viral carriers for the anti-adipogenic miRNA-27a. Cargo-free octadecylamine-containing NLCs and miRNA/cNLC complexes were characterized regarding particle size, size distributions, zeta potential, pH values, particle topography and morphology, and entrapment efficacy. Furthermore, the cytotoxicity and cellular uptake of the miRNA/cNLC complex in the 3T3-L1 cell line were investigated. The investigation of the biological effect of miRNA-27a on adipocyte development and an estimation of the accumulated Oil-Red-O (ORO) dye in lipid droplets in mature adipocytes were assessed with light microscopy and absorbance measurements. The obtained data show that cNLCs represent a suitable DDS for miRNAs, as miRNA/cNLC particles are rapidly formed through non-covalent complexation due to electrostatic interactions between both components. The miRNA-27a/cNLC complex induced an anti-adipogenic effect on miRNA-27a by reducing lipid droplet accumulation in mature adipocytes, indicating that this approach might be used as a new therapeutic strategy for miRNA mimic replacement therapies in the prevention or treatment of obesity and obesity-related disorders.

Premature babies and those born with a medical condition are cared for within the neonatal intensive care unit (NICU) in hospitals. Monitoring physiological signals and subsequent analysis and interpretation can reveal acute and chronic conditions for these neonates. Several advanced algorithms using physiological signals have been built into existing monitoring systems to allow clinicians to analyse signals in real time and anticipate patient deterioration. However, limited enhancements have been made to interactively visualise and adapt them to neonatal monitoring systems. To bridge this gap, we describe the development of a user-friendly and interactive dashboard for neonatal vital signs analysis written in the Python programming language where the analysis can be performed without prior computing knowledge. To ensure practicality, the dashboard was designed in consultation with a neonatologist to visualise electrocardiogram, heart rate, respiratory rate and oxygen saturation data in a time-series format. The resulting dashboard included interactive visualisations, advanced electrocardiogram analysis and statistical analysis which can be used to extract important information on patients’ conditions.Clinical Relevance— This will support the care of preterm infants by allowing clinicians to visualise and interpret physiological data in greater granularity, aiding in patient monitoring and detection of adverse conditions. The detection of adverse conditions could allow timely and potentially life-saving interventions for conditions such as sepsis and brain injury.