CMBEBIH 2019

Impedance cardiography (ICG) allows to measure parameters of heart mechanical function. ICG is sensitivity to movement artifacts inter alia breathing, which distorts impedance signal. Several methods were proposed to eliminate this distortion, but they cannot be used to continuous measurement or do not remove movement artifact. Adaptive filter is event-related, it learns signal characteristic within the cycle and removes components uncorrelated with the event. In this study, we compared ICG signal obtained during normal breathing with that after adaptive filtration and ICG signal obtained during momentary breath holding with this signal processed with adaptive filter. We conclude that adaptive filtering may help extract information from noisy and distorted ICG signal, but on the other hand, it may obscure some real changes in signal, for instance, rapid cyclic changes connected with respiration.

The aim was to validate the functionality and subjective experiences of timer-triggered electrical blink stimulation with participants (N = 6) suffering from dry eye symptoms caused by chronic unilateral facial palsy. In a stimulation condition, the muscles responsible for eye blinking were stimulated at fixed intervals while watching a video for about 120 min. In a control condition, the participants watched a video without stimulation. The participants rated their dry eye symptoms with a questionnaire before and after the both conditions. They also rated the levels of felt pain, discomfort and naturalness of the stimulated movement. Additionally, the magnitude of the stimulated eye blinks over time was evaluated. The results showed that the magnitude of the stimulated eye blink did not decrease significantly during the watching task. The stimulation was rated as painless, slightly uncomfortable, and fairly natural. The experienced eye dryness decreased significantly in the stimulation condition. Most participants got used to the stimulation, or even forgot it during the task. The findings are promising in respect to the use of timer-triggered blink stimulation.

Modern portable devices (e.g. wearables) provide technical support to record physical activity, which can assist various purposes, ranging from geolocation, step count, body temperature and biomedical parameters among others. These technological advances, the increase of literacy in health and also in informatics placed the smartphone and its massive use in the center of a new paradigm of monitoring physical activity. When combining these functionalities with the ability to communicate with remote entities, then it is possible to expand the use of smartphones, not only to monitoring physical activity but also to promote widespread adherence to physical activity programs. This paper presents the conceptual framework of a global health community program centered on a mobile application and a dedicated backoffice web application to perform physical activity prescription and supervision based on dashboards. The MOVIDA platform is comprised of 4 main modules, targeting different groups of the population. This platform enables exercise prescription, monitoring of user’s performance and adherence in metabolic diseases patients by MOVIDA.cronos, to specify and follow a cardiac rehabilitation program by MOVIDA.eros, to track and quantify indoor movements by MOVIDA.domus, and also access to a stratified training circuit, for maintaining or improve fitness level by MOVIDA.polis. In addition, this work reports the project main challenges from the conceptual phase of the technological platform to its development and implementation. This work can be useful for those who are starting a project with the same type of characteristics: multicentric, interdisciplinary and involving several partners in the community.

Cellular mechanobiology is highly important for tissue development and disease formation. However, lack of proper tools limit investigation of the cellular responses to different mechanical cues. High frequency (HF) vibration has already been applied in different cellular applications, but the knowledge of the stimulation effect on cells is limited. To meet this challenge, we designed a HF vibration stimulator for combined mechanical manipulation of live cells and high-resolution light-microscopy. Our system utilizes a commercial miniaturized speaker to vibrate a 3D printed sample vehicle horizontally. Technical tests demonstrated excellent performance at lower frequencies (30–60 Hz), enabling even high magnitude (HMHF, Gpeak ≥ 1 Gpeak) method. Real-time acceleration measurement and light-microscopy both revealed accurately and precisely produced low magnitude (LMHF, Gpeak < 1 Gpeak) vibrations. With our system, we could observe cellular responses to the LMHF (0.2 Gpeak, 30 Hz) vibration. In this paper, we introduce an inexpensive stimulation platform for the mechanobiology research of different cell applications.

Electromyographic (EMG) signals are used for the diagnosis of neuromuscular disorders. We have used machine learning algorithms in diagnosing neuromuscular disorders as a decision support system. Hence, in this study, for feature extraction DWT has been used and the Rotation Forest ensemble classifier has been used for classification. Furthermore, we also investigated the performance of different classifiers with Rotation Forest. The performance of a classifier is enhanced using the Rotation Forest ensemble classifier. Significant amount of performance improvement was achieved with a combination of Discrete Wavelet Transform (DWT), and Rotation Forest using k-fold cross validation. Experimental results show the feasibility of Rotation Forest, and we also derive some valuable conclusions on the performance of ensemble learning methods for diagnosis of neuromuscular disorders. Results are promising and showed that the ANN with Random Forest ensemble method achieved an accuracy of 99.13%.

The facts about the effects of high frequency electromagnetic fields (HF EMF) on human health are often controversial and incomplete. For this reason, the aim of this study was to examine impact of HF EMF on process of angiogenesis in eight rat organs of: pancreas, kidney, thyroid, liver, cerebrum, thymus, gastric gland and spleen. Wistar strain rats were exposed to HF EM fields with the following characteristics: 1.9 GHz frequency, 0.24 A/m intensity, electric field strength of 4.79 V/m, and SAR (specific absorption rate) value of 2.0 W/m2. Exposure time was 7 h per day, 5 days per week, over the course of 60 days. Our experiment was conducted on a total of 20 male rats divided randomly into two equal groups: one group of animals was exposed to HF EM fields as described above whereas, the other group of animals was not exposed to any HF EM fields. In our study histological and stereological analysis shows the results that volume density and number of endothelial cells of blood vessels increased with statistical significance in all organs of rats that were exposed to the HF EMF compared to the unexposed group. Increase in volume and number of endothelial cells in analyzed organs indicates the process of angiogenesis induced by HF EM fields, which can be used for therapeutic protocols.

Among a number of challenges present in monitoring systems, an efficient implementation of complex time-consuming algorithms and an identification of relevant features from gathered signals still gain high attention. Compared with the signals captured from human body, the problem of identification and classification of abnormalities in electroencephalography (EEG) and electrocardiography (ECG) signals is correlated to the diagnosis of a number of neurological, neuromuscular, and psychological disorders, such as epilepsy, sleep disorders, and similar. The problem of epileptic seizure detection based on EEG signal is discussed in this contribution. Special emphasis here is given to epileptic seizure detection using real-time signal processing based on Field Programmable Gate Array (FPGA) embedded platforms. Proposed approach involves an implementation of classification algorithm relied on Artificial Neural Networks (ANNs) on FPGA board, whilst the extraction of features from EEG signal is performed offline. Accordingly, real-time implementation of ANN-based approach and its comparison with conventional approaches with respect to accuracy, runtime speedup, and applicability to low-power consumption (wearable) devices is in the main focus. The implementation is based on benchmark data available from public repositories and loopback testing.

Imaging methods based on the physical phenomenon of speckle have been gaining relevance (mostly due to technological improvements in sensors and cameras) in several areas of science, particularly in the field of Medicine. Specifically, the use of speckle laser technology has proved to be useful in the characterization of post-hypoxia perfusion states, either in the cortex of animal models or in skin perfusion experiments. This dynamic information, if added to the morphology, results in an imagery modality that allows the full (static and dynamic) characterization of the scattered surface. In this work, a stereo vision system was adopted during a laser speckle acquisition of skin surface, in order to perform a dissimilarity (i.e. left vs. right) analysis based on activity descriptors in the context of a Post Occlusive Reactive Hyperemia (PORH) test. Additionally, to perform inter-view segmentation, a registration procedure is also proposed based on high entropy regions. The results reveal that among five commonly used activity descriptors, the Shannon Wavelet Entropy (SWE) is the most consistent in characterizing the transition from an occlusive state to a hyperemic state, thus indicating its use as a dissimilarity descriptor in stereo acquisitions to identify physiological states related with reduced perfusion and its recovery.

Microvascular perfusion is modulated by the breathing activity. However, to the authors’ knowledge, no study has attempted to assess the pathological deterioration of this physiological coupling in diabetes, which is related to structural and functional alterations of the microvasculature. On this basis, a phase coherence analysis was conducted to identify a possible weakening of the time-phase relationship between the breathing rhythm and the peripheral pulse, measured with laser Doppler flowmetry. Two groups of 21 healthy subjects and 21 type 1 diabetic (T1D) patients were evaluated in this retrospective study: a significant phase coherence was detected for the area beneath the diastolic phase of the peripheral pulse (median: 0.78; IQR: 0.20), in 81.0% of the controls; however, the analysis of the T1D group highlighted a considerable loss of synchronization, with significant values obtained in only 33% of the cases (median: 0.53; IQR: 0.15). This result may yield a valuable biomarker for the detection of diabetic microangiopathy.

Prostate cancer is a widespread disease among the male population. Its early diagnosis and prognosis are challenging tasks for clinical researchers due to the lack of very precise, fast and human error free diagnostic method. The purpose of this research is to develop a novel prototype of clinical management in diagnosis and management of patients with prostate cancer. Various classification algorithms were applied on a cancer database to devise methods that can best predict the cancer occurrence. However, the accuracy of such methods differs depending on the classification algorithm used. Identifying the best classification algorithm among those available is a difficult task. In this paper, the results of a comprehensive comparative analysis of nine different classification algorithms are presented and their performance evaluated. The results indicate that none of the classifiers outperformed all others in terms of accuracy, meaning that multiple classifiers can serve clinicians in diagnostic procedure.

Most common pathologic conditions in the alveolar bone derived from necrotic dental pulp are periapical inflammatory lesions (periapical granuloma and periapical cyst). The early diagnosis of lesions of the oral cavity is challenging for clinical practitioners. This research implements a computer-aided diagnostic system for classification of periapical inflammatory lesions in order to improve quality of diagnosis and planning of treatment. A data set was obtained from Department of Oral Surgery, School of Dentistry, University of Sarajevo and contains 13 input parameters. Our results demonstrated that usage of Random Forest algorithm can increase true diagnosis to 85.71%. It has also been shown that this accuracy can be achieved with fewer number of input parameters by keeping high detection accuracy for both cysts and granulomas. A developed computer aided diagnostic system with a proven accuracy can be used for a creation of a user interface that will increase quality of diagnosis and planning of treatment.

In this paper we present educational application illustrating vectorcardiogram and its relation to the heart cycle and recorded ECG signals. In contrast to commonly used visualizations of the ECG signal, 3D animations of vectorcardiogram are not frequently used. The vectorial analysis is important for understanding link between the cardiac abnormalities and the characteristic shapes of the ECG. The vectorcardiogram animation is implemented in Python and based on the publicly available conventional 12 lead ECG signals accompanied with simultaneously measured 3 Frank lead signals. Students can iterate through the signals reviewing temporal change of cardiac vector and ECG vectors of the main limb leads, displaying the QRS, P and T loops per cardiac cycle, and displaying QRS cardiac axes.

Multiscale entropy is successfully used to measure dynamical complexity of a finite length time series of different physiological data, including the heart rate. It is shown that the multiscale entropy as a measure can be used to discriminate healthy subjects from subjects with pathological conditions. In this paper we evaluate possibility to apply multiscale entropy to shorter heart rate time series and to evaluate resources needed to implement the algorithm in C, and to assess if it is possible to run the algorithm on a specific DSP platform.

Alzheimer disease is one of the most prevalent dementia types affecting elder population. On-time detection of the Alzheimer disease (AD) is valuable for finding new approaches for the AD treatment. Our primary interest lies in obtaining a reliable, but simple and fast model for automatic AD detection. The approach we introduced in the present contribution to identify AD is based on the application of machine learning (ML) techniques. For the first step, we use histogram to transform brain images to feature vectors, containing the relevant “brain” features, which will later serve as the inputs in the classification step. Next, we use the ML algorithms in the classification task to identify AD. The model presented and elaborated in the present contribution demonstrated satisfactory performances. Experimental results suggested that the Random Forest classifier can discriminate the AD subjects from the control subjects. The presented modeling approach, consisting of the histogram as the feature extractor and Random Forest as the classifier, yielded to the sufficiently high overall accuracy rate of 85.77%.

The purpose of this study is to make a dosimetric analysis of the overlapping and gap areas in the case of a cranio-spinal irradiation. A simulation of the overlaps and gaps was performed on a treatment planning system. The overlaps and gaps were simulated for the 2, 4, 5, 6 and 8 mm overlaps or gaps. The data recorded: global and local maximum of doses, depth of the 95, 100 and 125% dose, the depth of spine location in the overlapping/gap areas. The local maximum values were increased up to 7.03 Gy in the case of the cranial-upper spinal field overlaps and up to 5.45 Gy in the case of the upper-lower spinal fields. The gaps cause the decreases of the local maximum values up to 6.65 Gy in the case of cranial-upper spinal field. An increase of the depth of 125% isodose line of 1.04 cm in the case of the 5 mm upper-lower spine fields overlapping was recorded. The total coverage of the target volume by 125% isodose line, in the case of the 5 mm + 5 mm overlapping between the cranial and the upper spinal field may be a source of a damage of spinal cord. The partially covered treatment volume by 95% isodose line in the case of 4 mm + 4 mm and 5 mm + 5 mm gap area between the cranial and the upper spinal field, may cause a relapse of the tumor.

This study is aiming to investigate the contribution of phase contrast breast tomosynthesis, in image quality and detectability of mammographic findings, using a breast phantom within a highly heterogeneous background incorporating details that mimic various breast lesions. A physical phantom was constructed with complex background composed of egg white part and lard, mimicking a breast with 40% glandular—60% adipose tissue. Nylon spheres and CaCO3 specks simulating masses and microcalcifications respectively, were embedded into the mixture at different depths. Mammographic and tomosynthesis images of 44° acquisition arc were obtained, in phase contrast mode with two different object to detector distances of 50 and 150 cm. The experiments were performed using synchrotron radiation at 20 keV within the conventional mean glandular dose (MGD) range. Line contrast measured across two of the mammographic findings was used as evaluation metric, in order to assess quantitatively the detection of breast abnormalities and the image quality from the different modalities. Visual and quantitative assessment of the images acquired, showed that the increase of object to detector distance resulted in superior contrast and stronger edge enhancement for both low and high contrast features. Tomosynthesis images eliminated the overlapping effect and made the in-depth localization of structures possible. Specifically, in case of the low contrast features, the smallest sized mass was hardly detected in the 2D images while it can be well visualized in the BT tomograms. Results of this study showed that tomosynthesis phase contrast imaging is a promising technique that can be proved important for the detection of small details in breast screening and diagnosing.

Hounsfield units (HU) are a dimensionless units universally used in computed tomography (CT) scanning to express CT numbers in a standardized and convenient form. Calibration curve (CC) implemented in radiotherapy treatment planning system (TPS) shows the dependence of HU on relative electron density (RED). Radiotherapy treatment planning process is based on data from the CC and linear accelerator (Linac) data set. RED is constant and specified for each material, but the HU can change depending on several factors. Dosimetric phantom in radiotherapy properly represents human anatomy and enable thorough analysis of both the imaging and dosimetry system. For the purpose of CC checking, two phantoms were used: Catphan 504 (The Phantom Laboratory) and CIRS 062MA (Computerized Imaging reference Systems, Inc.). The aim of the paper was to check whether the HU depends on the dimensions of the phantom. Catphan 504 phantom was scanned first, in order to verify the HU determination methodology. After that, CIRS 062MA phantom representing both abdomen and head configuration was scanned. By analyzing Catphan 504 phantom obtained scanning results, it was concluded that the HU values are correctly determined, since the results are in accordance with the manufacturer’s recommendations. Based on results of CIRS 062MA phantom scan, the HU dependence on the CT simulator tube voltage was confirmed. Significant difference in HU for high density materials (up to 135 HU) due to different phantom sizes was observed.

Aim To determine the impact of decreasing patient dose on image quality or diagnostic information during diagnostic thorax examination using computed tomography/CT/at University Clinical Hospital Mostar/UCH/. Methods Images were acquired using a CT General Electric LightSpeed 16 slice scanner. There were 62 adult patients with different input diagnoses involved in this research, which lasted from March 1st 2018 to June 1st 2018. After determination of patient dose, the objective was optimization of protocol parameters for the purpose of lowering the dose received by patients, in a manner that does not jeopardize image quality or diagnostic information. A thoracic radiologist using a double-stimulation method assessed image quality according to the European Guidelines on image quality criteria for CT 16262/EUR16262 EN/, followed by calculation of dose efficiency factor figure of merit/FOM/. Results Changing the protocol parameters enabled a significantly decreased patient dose. Visualization of pulmonary anatomical structures was not significantly changed by decreasing the dose. The mean FOM before optimization was 1.28 mSv−1 and 2.46 mSv−1 after optimization (p < 0.001). Conclusion By changing the parameters of the protocol a significant dose reduction was achieved without affecting the diagnostic information.

The chest radiography is the most valuable imaging modality in the assessment of respiratory problems in neonates. However, use of X-rays is associated with exposure to ionising radiation. Scattered and leakage radiation increases over-all dose received by each patient in the ward. In this study we explore medical and public exposure of patients in neonatal intensive care unit (NICU) in the Clinical Centre of Sarajevo University (CCSU). Study included 120 randomly selected patients. The effective dose arising from medical and public exposure was estimated using direct measurements and appropriate software tools. The entrance surface air kerma for a single chest radiography exposure is 86 μGy, which corresponds to 0.60 mSv effective dose. On average, patients are exposed 2.1 times, so the average cumulative effective dose is 0.13 mSv. The estimated effective dose from public exposure was $$ 1.25 \times 10^{ - 4} $$ 1.25 × 10 - 4 mSv, which could be considered negligible. For patients undergoing more examinations, one could consider introducing ultrasound (LUS) as a method of choice.

Positron emission tomography (PET) is a diagnostic imaging modality in nuclear medicine. The most common radionuclide in PET is 18F fluoro deoxyglucose (FDG). In this study we used the information on radionuclide uptake from PET images and software to make an estimation of effective dose received by patients during 18F-FDG PET examination. We analysed data from 50 patients who performed positron emission tomography—computed tomography (PET-CT) examination. Uptake values were collected in bladder, bones, heart wall, kidneys, liver, brain and remainder. Using a simplified biokinetic model, residence time was calculated and used as an input parameter in OLINDA/EXM® software package. The conversion factor from administered activity to effective dose was found to be $$ 0.016\frac{{{\text{mSv}}}}{{{\text{MBq}}}} $$ 0.016 mSv MBq , which is only 15% less then value found in literature. The method described in the paper might be suitable in situations when standard calculation models are not adequate.

Computed tomography (CT) is an imaging procedure that uses X-rays to create detailed pictures, or cross-section scans, of areas inside the body. Benefits of the CT have been proven over the past decades, but they come with a price high radiation doses to patients. Understanding how doses depend on technical parameters is a necessary step towards an optimized imaging procedure. Aim of this study was to assess the air kerma distribution and size of the X-ray beam of a conventional computed tomography scanner.

Fractal analysis of grey-scale digital image is a recognized tool for detection of irregularities in the image and as measure of complexity of the image. Basic idea of this paper is to explore relation of fractal dimensions and some other related parameters in the chosen regions of interest (ROI) of grey-scale digital medical image with corresponding specific tissue characteristics. If difference of the values for calculated parameters is proven to be statistically significant for ROI of mammograms with different specific characteristics, this kind of analysis can be helpful for computer aided diagnostics. Especially, possibility of automatic detection of microcalcifications is considered. Analysis of mammograms in this manner is not a simple task, as there are four different types of parenchym tissue, there are five grades for microcalcifications according to their malignity (BI-RADS), and there are several different types of microcalcifications. Results of fractal and multifractal analysis of 131 ROIs (150 × 150 pixels) from 60 different mammograms are presented in this paper. Out of total 131, 60 ROIs encloses normal tissue (without dense masses or microcalcifications), and remaining 71 ROIs encloses tissue with microcalcifications. Out of total 60 mammograms concerning parenchym tissue type, 17 mammograms is for ACR 1 structure, 21 ACR 2, i 22 ACR 3 structure. Fractal parameter that is considered is Hurst coefficient, and it is considered how it changes with size of ROI. $$ {\text{H}}{\ddot{{\text{o}}}}{\text{lder}} $$ H o ¨ lder exponent and multifractal spectra for each ROI is calculated, and corresponding histograms are analyzed. Values of suitable parameters from these histograms are tabulated to check their statistical dependance on ACR and BI-RADS grades. Zero hypothesis that there is no difference between normal ROI and ROI with microcalcifications is tested.

Aortic stenosis [AS] is set on the forth place of all cardiovascular disease in western world. Severe aortic stenosis [SAS] is one of the most common disease that in treatment demand cardiac surgery—replacement of native aortic valve with mechanical or biological prosthesis in our environment. SAS is often a consequence of a relapsed rheumatic heart disease. This paper present the possible modality of diagnosis SAS. Testing was done on 107 samples, 70 samples were SAS, and the rest of 37 were patients who were sent to some another examination, after ultrasound was done and diagnosis of SAS was excluded. In this paper, the application of basic kind of ANN architecture—the feedforward networks with backpropagation training—is explained, since this structure is able to perform nonlinear multiple regressions in a reliable manner, avoid overfitting. Dataset consists of 12 parameters as shown in Table X; sex, age, dizziness/loss of consciousness, dyspnoea, palpitation, systolic murmur of AS, EF, AV morphology, AVVmax, AVPGmean, AVPGmax, Area. Although limited number of data were present in this study, such automated systems can be used as assistant tool during diagnosis in real-time clinical settings. In the future it is planed to test and use this automated system for classification of aortic stenosis.

The introduction of portable hand-held X-ray devices opened a new chapter in dental radiology. The strict border between the controlled and supervised areas ceases to exist. The aim of this paper is to measure the dose rate around a portable dental X-ray device, as well as to provide spatial distribution of the ambient dose equivalent of scattered radiation. Results also include measurements of X-ray tube voltage, incidence air kerma, exposure time, half-value layer and total filtration according to the international standard IEC 61223-3-2:2015 Evaluation and routine testing in medical imaging departments for the quality control of dental X-ray devices. Measured values of incidence air kerma indicate the values of the patient doses which are much lower than existing national diagnostic reference values.

This paper discusses the diagnostic performance of the modern medical thermal imaging system with the other imaging modalities for breast cancer detection. In this study, the digital infrared thermal imaging system is used for analyzing the thermal images of the 270 breast patients diagnosed by the conventional imaging techniques. The thermographic images of these patients are analyzed and then classified according to the 6 different BI-RADS categories by means of the asymmetry analysis technique based on the commonly used 11 statistical features. Finally, higher sensitivity, specificity values and higher accuracy rates are obtained for the 270 breast patients.

Microneedles, tiny micron-sized structures, made of a variety of materials, have been recently developed for a painless and safe transdermal delivery of drugs through the skin. While microneedles minimally disrupt the outermost layer of the skin and create a pathway to deliver the therapeutic agents, they could also act as conduits for biosignal sensing. Microneedle-based sensors made of conductive and electrochemically reactive biomaterials can provide the valuable information on the levels of analytes in the blood. Also, researchers have realized the great potential of microneedles integrated with microelectrodes for extraction of interstitial fluid and capillary blood, for enhanced monitoring of patient health. Furthermore, they could serve as a tool for analysis of complex medical conditions and illnesses. This microneedle sensor technology can provide a sophisticated analytical approach for in situ and simultaneous detection of numerous analytes. The microneedles can also be used to measure metabolites, biomarkers, and drug level in the interstitial fluid and capillary blood, as well as for the use of microneedle array technology as biosensors for continuous monitoring of analytes in body fluids.

This review summarizes types of electrochemical biosensors used for hormone analysis and provides overview of their characteristics for medical applications. Comparison between different types of electrochemical biosensors used in: insulin, cortisol, testosterone and thyroid-stimulating (TSH) hormone is represented. Focus is on the linear range and the limit of detection (LOD) of biosensors used for detection of various hormones. According to the before mentioned hormones, similar categories of biosensors deliver correlating results in terms of linear range and LOD.

Within the realm of genetics, bioengineering and especially microbiology, it is often necessary to develop and grow a certain type of microbial culture for purposes of investigating certain microbiological phenomena or conducting a research. In order to perform the process of incubation, it is required to maintain a constant temperature for the time frame within the range of 24–48 h, depending on the type of bacteria under investigation. The device which enables us to grow such group of microorganisms is called a microbiological incubator. Two crucial parts in the microbiological incubator are heater and temperature sensor. Usually, such incubators have one chamber, whose temperature is controlled by a microcontroller. This project aims to improve the functionality of regular microbiological incubators by designing one which will have two separately controlled chambers and therefore be more functional than a conventional one. The incubator will be controlled with NodeMCU platform with integrated Wi-Fi module, so it will have IoT prefix, which basically means that one will be able to control it and to obtain certain data from it via the internet.

Free-flying honeybees can electrostatically collect particles from air in the flying and foraging areas, which in conjunction with organic-based explosive vapor sensing films, placed at the entrance to the beehive, can be used as a passive explosive sensing mechanism. Moreover, bees can be trained to actively search for a smell of explosive. Using trained honeybees in conjunction with a system for honeybee localization enables generation of a spatial-time honeybee density map, where the most visited places point to suspicious areas. In both methods (passive and active), bees’ activity monitoring plays a significant role, providing information about environmental parameters and activities of bees at the entrance and exit of a beehive. In this paper we present the design and realization of an electronic system for bee activity monitoring at the front of a hive while using bees for explosive detection. The system also monitors air temperature and relative humidity. Results obtained to date from activity monitoring are useful in planning testing activities within our active and passive method, as it can determine the optimal period of the day and environmental parameters in which bees are most active.

Bees immensely contribute to mankind. Over the years, bees have performed a task that is vital to the survival of agriculture and pollination. One third of our global food supply is depends on bees’ pollination, which simply means that bees keep crops and plants alive. If bees were to go extinct, mankind would not survive because the food we eat depends on bees’ pollination. Humans can only last for four years without bees. Monitoring of bees should be a priority. This is one of the reasons why HaBEEtat has done research to create a platform that helps beekeepers keep bees safe. The objective of HaBEEtat is to remove the greatest threat to bees’ lives, which is climate change. HaBEEtat has created a platform that is going to help beekeepers to monitor the temperature, humidity and weather, which will help to preserve the lives of millions of bees. The platform will thereby decrease the declination of bees and increase their population, as well as production.

Elastomeric infusion pumps have found widespread application for the long-term administration of drug treatments. Nevertheless, their actual reliability is debated; thus, the development of integrated monitoring systems, able to provide an accurate, continuous assessment of the drug infusion dynamics, is of extreme relevance. The present work briefly introduces a prototype system which estimates the volume of the drug solution, by measuring the relative distances from the wall of the reservoir, during the emptying time.

This paper presents an IMU-based wireless wearable system for real-time three-dimensional measurement of spinal deformities in a noninvasive manner. Applications of the proposed system range from diagnosis of spine abnormalities to postural monitoring, on-field as well as in a lab setting. The system is comprised of one wireless and 26 sensor nodes wired along to form a lightweight wearable sensor stripe for superficially attachment above human spine. The nodes size and arrangement is optimized so that each node to approximately track an individual vertebra. All sensors communicate to the main unit through I2C bus in a daisy chain fashion. Spine is modeled as a compound flexible with 26 segments allowing dynamic measurement of three-dimensional spine motion, which is animated and monitored in real-time using dedicated Android application with interactive GUI. The proposed system detects Kyphosis, Lordodis and Scoliosis and calculates the related Cobb angles. It can be integrated in wearable chest harness and is highly suitable for both diagnose spinal deformities in early stages and follow up the progress of the spine.

Nanotechnology is one of the most promising science and technology discipline that targets to bring new solutions for many applications in biotechnology, biomedical, energy and cosmetic industry by improving particles and devices scale of nanometers. Various sized and shaped nanoparticles can be synthesized by several methods. Up to now, scientists prefer physical and chemical fabrication of nanoparticles. But, these methods contain use of toxic, expensive and non-environmentalist solvents, reducing and stabilising agents. For a sustainable science, there is a necessity development of more eco-friendly, cost-effective and trustable alternative processes. In this context, using biological sources as reaction agent, have a strong potential. Plants, bacteria, fungi are essential biological sources for transformation of metals to nanoparticles. Many researchers focus on fungi and bacteriological potential in nanofabrication whereas algae are highly intriguing biological systems in nanotechnological approach. Some of cyanobacteria and algae have previously been used to synthesize intracellular or extracellular metal nanoparticles. Most of the research concentrate especially on gold and silver nanoparticle production from algae. In this work; bioreduction of silver, zinc and iron metals have been investigated using culture supernatant of marine algae Schizochytrium sp. For characterization of nanoparticles, UV visible spectroscopy, zeta sizer were used. Nanoparticle size was determined by zeta sizer and particles’ surface plasmon resonance band detected by UV-Visible Spectroscopy.

Green synthesis of nanoparticles has recently been a preferred method since it offers useful approaches such as non-toxic, biocompatible, environmentally friendly, cost-effective, stable product and trustable alternative processes compared to other methods. Various biological sources such as plant, algae, fungus and bacteria are widely used in biological synthesis of nanoparticles. Algae are more adapted organisms compared to the others for having high growth rate and biomass productivity, high heavy metal accumulation capacity, etc. Nanoparticles can be used in various area such as antimicrobial, antifungal, antioxidant agent, admixture of biosensor and drug transport/release, also diagnosis and treatment systems. Since each organism has different biochemical composition and metabolic pathways, their synthesized nanoparticles are going to show various characteristics and application area. In this study, silver, iron (II) and zinc nanoparticles were produced by using microalga Galdieria sp. The synthesized nanoparticles were characterized by using UV visible spectroscopy, Fourier transform infrared spectroscopy (FTIR) and zeta sizer. Antimicrobial activity against gram negative and gram-positive bacteria was also examined throughout the study. In conclusion, the potential of this biogenic nanoparticle was discussed.

In this paper, a system of ordinary differential equations, which describes the interaction of HIV and T-cells in the immune system of the human body, is used for infection modeling. The goal of this approach is better understanding of HIV immunology for the purpose of improving the existing models and testing different treatment strategies. Possible use of nanotechnology and micro/nanorobots, as future technologies that will make HIV treatment more efficient, are considered as well.

The recent intensive technology advancements fuel innovation in every area of modern society. Nanotechnology together with biotechnology, and ICT (Information and Communication Technology) represents a technology triad that has the potential to revolutionize every aspect of our lives in the 21st Century. The unique and fundamentally different physical, chemical, electrical, mechanical and biological properties of nanomaterials from the properties of largersize bulk counterparts, enable the fabrication, characterization, and the manipulation of functional and intelligent materials, devices, and systems opening a whole new universe of the applications. In the nanotechnology industry, which is expected to reach USD 132.41 by 2023, it is crucial to adequately market a product, service, or even new technology in order to successfully position it. The environment in which businesses operate is characterized by numerous competitions, products, dynamic and rapid changes, strong technology development and increasingly demanding consumers. Consumers are at the center of marketing activities and therefore it is crucial to get to know the consumers and establish a long-term relationship with them. It can be anticipated that economic expansion will lead to the rise of the nanotechnology sector through the stimulation of consumers and industry to use a wide range of nanotechnology-enabled products. Therefore, this paper deals primarily with the analysis of how nanotechnologies affect marketing and measure consumer satisfaction that is crucial to the success of the enterprise in this industry. Nanotechnology’s influence on sustainability is presented as well.

In this paper we have applied theory of exciton on the ultrathin molecular dielectric films—layered nanostructures with the thickness up to 20 atomic layers. We have calculated optical properties: the absorption, reflection and transparency indices as the function of frequencies of external electromagnetic field in near IR region. We showed that one of the significant properties of the ultrathin film is their interaction with substrate or environment, which could be represented through perturbation parameters. For symmetrically perturbed films, all optical properties depend on the position of the crystal plane with regard on boundary planes of the film. We have analyzed optical properties for the whole film structure based on the consideration for multiple reflection, absorption and transparency. The theory has been applied for the four-layered dielectric nanofilms with various different boundary conditions on film surfaces. As a result, we obtain some discrete resonant absorption lines, where their number, position and distribution strongly depend on the boundary parameter values, i.e. on the type and the technological process of their preparation/fabrication. While balk made from the same material totally absorb the near IR region, in ultrathin films will appear only selective and discrete absorption (also with reflection and transparency too). These results could be used in optical engineering of nanostructures and technology of designing of new electronic, photonic and photovoltaic devices. In addition, particularly designed nanoparticles are used in nanomedicine, whose behavior strongly depends on external electromagnetic field, in purpose of drug carry or delivery.

In this paper, the possibilities of efficient targeted delivery of drugs by using nano-devices are pointed out, with special emphasis on the physical properties of used materials. Particular attention was paid to the analysis of the phonon subsystem in the above-mentioned structures since it is expected that it can play a significant role in the transport and release of drugs, as well as in the biodegradation of the carrier nanomaterials. Nano-devices used as carriers also need to have properties that make them suitable for biomarkers so that they can be transferred to precisely defined sites in the body. This reduces the side effects of drugs and increases the efficiency of their use.

Zeolites are one of the most interesting areas of nanotechnology. They have wide application because of their properties, so they are also used for microneedles for delivery of various drugs. Until now, they have been used for the delivery of insulin, diclofenac and ketoprofen and our work will reveal collagen delivery capabilities and thus the application of zeolite microgels in the application of anti-age preparations based on the comparison of insulin molecule characteristics and collagen molecules. Since it is a preparation that is increasingly used in cosmetology and dermatology, we also find out how the best microneedles made of zeolite are applied for delivery of collagen and explain the application of dermaroller and dermapen with this microneedles.

The need for accurate and reliable methods for food analysis on molecular level has been steadily increased during past decades. This trend is connected with the recent food scandals caused by food adulteration. Raman spectroscopy has very important role in identification of food fraud and food adulteration. Through this specific technique, the food quality control and authentication of food products can be easily performed. Adulteration, contamination and origin of food can be investigated through new field of food science-food forensics. Raman spectroscopy is one of the most valuable spectroscopic techniques used in different research fields. It has gained popularity due to it’s advantages over other analytical techniques. It is used in chemistry to study vibration, rotational, and other low-frequency modes of the system. This technique allows obtaining a chemical information from samples in nondestructive manner. It is useful for both solid and liquid samples. The main advantage of the Raman spectroscopy is that samples doesn’t require preparation. Another advantage is that water does not interfere in analysis. Raman spectra is captured within few seconds from sample, and after that analysed. In this review, relationship of food forensics with Raman spectroscopy is briefly explained. Raman spectroscopic techniques such as Fourier transform Raman spectroscopy, Surface-enhanced Raman spectroscopy and Visible—micro Raman spectroscopy are briefly introduced.

The nature derived therapeutics is getting intense attention rather than chemical synthesis and synthetic ones. Today the expansion of natural bioactive molecule market is started to be dominated and generic drug and therapeutic understanding looks like to leave its place to a new horizon. Thus, natural originated therapeutics under controlled production conditions are of importance. Besides the public attention on natural molecules are also gain advance and the demand on this bioactive molecules is also increasing dramatically. The bioactive molecules from microalgae show antioxidant, antibacterial, antiviral, anticancer, skin regenerative, sunscreen, antihypertensive, neuroprotective and immunostimulatory effects which are favorable for pharmaceutical, nutraceutical and cosmetics industry. Also a new concept known as functional nutrition also broaden the acceptability and utilization of microalgae derived bioactive metabolites in new dietary formulations. The expansion of microalgal biotechnology and the number of research gained from the role of biologically active microalgal metabolites display the emergence of the microalgae farming for new pharmaceutical formulations. In this study, we prepared solvent and water extracts of G. sulphuraria, N. texensis, S. bacillaris, E. carotinosa, C. minutissima, S. limacinum, C. cohnii, and C. vulgaris. Antioxidant activity using DPPH radical scavenging activity and total phenolic compounds were measured from the methanolic extracts and water extracts. With the bioactive extracts cytotoxicity test were performed on Hep-G2 and B16-F10 cell lines. The results display potential onset of novel therapeutic compounds derived from microalgae.

Biofilms are microbial mono-specie or multi-specie (consortium) communities that play a significant role in the clinical, industrial and natural settings. Biofilm formation can be determined by using qualitative and quantitative tests, where the latter are considered more reliable. The prominently accepted result interpretation procedure for quantitative tests includes the calculation of optical density cut off value (ODc) followed by the determination of biofilm forming categories using formulas. This procedure is time consuming and many laboratories resort to the use of less reliable tests to conduct biofilm formation analysis. This is where Machine Learning (ML) could play a significant role. In this study Random Forest Classifier has been applied to a dataset of 960 bacterial isolates, where biofilm formation was tested using the spectrophotometric assay and biofilm categorization was carried out using formulas based on ODc calculations. The proposed model, based on the Random Forest Classifier, achieved the classification accuracy of 96.35% and the classification error is a bare 3.65%. Absolute and relative errors of the prediction model are 0.208 ± 0.167 and 20.82% ± 16.72%, respectively. Finally, the correlation coefficient between the predicted and actual value is 0.980. This paper illustrates how ML could be used to determine the biofilm forming categories and as such aid in the development of a unique standardized procedure for the evaluation of results obtained by quantitative tests of biofilm formation.

In this study, the vertical component of the ground reaction force (GRF), the maximum pressure value and the center of pressure (COP) motion in the longitudinal direction during stair climbing with and without a handrail have been determined. The measurement was carried out using the zebris FDM-S measuring system. For both climbing modes (NH—no handrail, H—handrail) the maximum and minimum values of the vertical component of the GRF were achieved in approximately equal percentages of the stance period (SP), with the greatest influence of the handrail use at the first maximum value. The COP position provides important information about a person’s postural control during locomotion. It has been found that in the case of climbing with a handrail, the COP position is moved more anteriorly, indicating a greater inclination of the entire body forward. The analysis of the maximum pressure values showed two pronounced maximums with one minimum between them. The impact of the handrail use on reducing the pressure is most evident in the area around both maximum values.

The locomotion of people with amputation is slower, less stable and requires more metabolic energy than the locomotion of physically fit individuals. Individuals with amputation of the lower extremities fall more often than able individuals and often have difficulty moving on uneven terrain and stairs. These challenges can mostly be attributed to the use of passive mechanical prosthetic legs that do not react actively to perturbations. Latest submitted solutions for active prosthetic devices of the lower extremities can significantly improve mobility and quality of life for millions of people with lower limb amputation, but challenges in control mechanisms of such devices are currently limiting their clinical viability. In this paper we present a prototype of an above-knee prosthetic leg with active knee and ankle joints while using the proposed robust control law.

This paper is sequel of the previous research about determining blood flow through new designed stent graft in abdominal aorta. The goal of this research is to show that a very short stent graft can significantly reduce pressure in the abdominal aorta, which can lead to savings in operating time, material and lower the quantity of artificial materials in the body of the patient. Methods of Computation Fluid Dynamics (or shorter CFD) were used to determine characteristics of blood flow in the abdominal aorta. CFD is a powerful tool, used for solving fluid flow problems in a variety of engineering disciplines such as hydraulic engineering, mechanical engineering, meteorology, environmental engineering, biomedical engineering and many more. During a CFD simulation, the fluid flow domain is divided in smaller sub regions. Afterwards, the governing equations of fluid flow are solved for each particle in an iterative process, which is conducted till the accomplishment of the desired residual error. After completing research regarding shortening of the existing length of stent and work based on 2d check ups and simulations we decided to do 3d models to try to confirm objectivity of the results. Comparing 2d and 3d results the clearer interpretation of results and design was shown. This confirmed the thesis that smaller stent dimensions can also present adequate treatment for this clinical state.

Offering many fundamental and practical advantages of relevance for today’s chemical and biological industry, microreactors are rapidly replacing round-bottomed flasks in modern biochemical labs. Compared to the batch processing, microreactors can offer precise control of reaction variables, high-throughput scanning of reaction conditions, increased safety parameters and they require small quantities of reagents. These miniaturized devices are widely used to facilitate routine work in biochemical analysis and also have applications in biocatalysis where they are termed as enzymatic microreactors. In this work, enzymatic microreactors are used to ease characterization of CaLB enzyme activity as a function of a substrate concentration. The work demonstrates potential of Lab-on-a-Chip devices with enzymatic microreactors as an evolving platforms for performing reliable on-chip biocatalyctic measurements and a possible foundation for future flow-chemistry based industrialization.

Voltage imaging allows to visualize the propagation of the action potential while it propagates in cardiac tissue. In our experiment we acquire a stack of voltage images, using a fluorescence microscope. In this work we focus on the development of a model of the signal and on the estimation of its parameters. We assumed the signal can be represented as the sum of two exponential functions, starting from the instant of activation of the cell. Results indicate the model is able to adequately describe the shape of the waveform, despite the high noise level in the original images.

Atherosclerosis is a disease of arterial blood vessels characterized by the accumulation of lipids in the arterial wall, starting with endothelial dysfunction, which favors lipid and cell elements crossing inside blood vessel wall. In this study, using DICOM images, a numerical model of atherosclerosis progression was developed. Fluid domain (blood) was modeled using Navier-Stokes equations in conjunction with continuity equation, while the solid domain (arterial wall) was modeled using Darcy’s law. For the purpose of modeling lowdensity lipoprotein (LDL) and oxygen transport, convection-diffusion equations were used. Kedem-Katchalsky equations were used for coupling fluid and solid dynamics. Determination of plaque location and plaque volume with computer simulation for a specific patient shows a potential benefit for prediction of disease progression. The results for plaque concentration for the right and left coronary arteries are presented.

Background Atherosclerosis is chronic disease, the prevalence of which has increased steadily as the population ages. We assessed prevalence, quality, and extent of coronary atherosclerosis using coronary angiography in a group of diabetic patients compared to nondiabetic patients. Methodology One hundred patients with suspected coronary artery disease underwent coronary angiography of the right coronary artery (RCA) and the left coronary artery (LCA) and were tested for the differences between diabetic (50) and non-diabetic (50) patients in ischemia detection by this method. All patients underwent coronary angiography in Heart Centre of the Clinical Center University of Sarajevo in period from January 2012 to January 2015. Coronary angiography was performed in the right and left anterior oblique position. Results Significant differences in sedentary lifestyle, and hypertension were seen among the diabetic and the non-diabetic group. Development of critical and diffuse coronary artery lesions was significantly higher among diabetics than non-diabetics. Changes in the proximal segment of the left anterior descending artery were the most common finding in diabetic patients. Stenotic atherosclerotic lesions of the large coronary arteries were significantly more common in the left than in the right coronary artery, but the difference between the diabetic and the non-diabetic group did not reach statistical significance. The most frequently atherosclerotic lesion of the RCA was seen in the middle segment, rarely in the proximal and distal part. Conclusion Diabetic patients were found to have a significantly higher prevalence of stenotic atherosclerotic lesions of the coronary arteries. Diabetes significantly affects the anatomy of coronary arteries, and is associated with age, sedentary lifestyle, and hypertension. These findings may prove clinically useful in the follow-up of diabetic patients, the choice of diagnostic procedures as well as in active treatment either by atherectomy or by percutaneous angioplasty and stenting.

Introduction The advanced bolus options improve glycemic control of patients with type 1 diabetes (T1D) on insulin pump (IP) therapy. This is extremely important for the patients who do not use CGM (continuous glucose monitoring) regularly. Objective To compare the difference in the parameters of glycemic control (HbA1c, postprandial increase of blood glucose and number of hypoglycemic episodes per week) between the group of patients who use bolus calculator for <50% of the total daily boluses and the group the patients who use bolus calculator for ≥50% of total daily boluses. Patients and methods The study included 41 patients aged over 18 years with T1D on IP therapy in Republika of Srpska. All patients used IP for at least one year prior to participation in the study. Before the IP therapy was initiated, all the patients were trained for carbohydrate counting in course of flexible insulin therapy training (FIT). Professional software, CareLink Pro® Software (Medtronic Inc., Northridge, CA, USA) was used to download data from insulin pumps to a personal computer. The default frequency of bolus calculator use was ≥50% of total daily boluses. Results No statistically significant difference was found in HbA1c (6.61 ± 1.10 vs. 6.77 ± 0.97, p = 0.624) or the number of hypoglycemic episodes (2.00 (1.00, 4.00) (1.0–6.0) versus 3.00 (2.00, 3.50) (1.0–5.0), p = 0.322) between the group of patients who have used bolus calculator for <50% of the total daily boluses and the group of patients who used bolus calculator for ≥50% of total daily boluses. Patients who have used bolus calculator had significantly lower postprandial increase in blood glucose after breakfast. Conclusion Among the patients with T1D on IP therapy, who do not regularly use CGM the use of the bolus calculator and use of different types of boluses, can improve glycemic control on IP therapy.

Today, endovascular prosthesis—stents are used as a solution for treating many health disorders and diseases. Their major application is found in treating cardiovascular diseases. One of the problems in stent implantation is a process called in stent restenosis (ISR). In the pre-stent era, the occurrence of restenosis ranged between 32 and 55% of all angioplasties, and in bare-metal stent (BMS) era this range dropped to 17–41%. Many factors have influence on this phenomenon. Some studies show that in stent restenosis, strut shape and thickness have significant impact, especially if the stent is implanted in the small arteries. For better stent geometry modeling, in this paper authors suggested novel approach—parametric optimization on the existing stent design. For evaluation of the parametric optimization and mechanical performance of nitinol stents as well as comparison of differences between old design (non-optimized) and new optimized design the finite element method was used. Simulation was performed assuming that the stent devices used for this research were made by laser cutting, from tube form, by application of expanding and crushing force. The behavior of two different stent models was analyzed: old Palmaz-Schatz design and novel optimized design. Novel design based on the results from parametric optimization preceded on the Palmaz-Schatz design. Performed simulation on stent models showed that the new modern design has better clinical behavior due to lower contacting surface, higher radial resistive strength and much better superplastic behavior. Optimization process was based on two optimization rules: minimization of the model volume and provide the best possible strain field in the model. Comparison of result from FE analyses from old an optimized design show that based on this approach it is possible to engineers in the future create a new and much beater stents very easy.

The main purpose of this study was to computationally examine the hemodynamic parameters of plaque progression within carotid artery, such as wall shear stress and plaque concentration. The 3D finite element mesh was created for a patient-specific anatomical geometry which was reconstructed on the basis of computed tomography (CT) scan images. The 3D blood flow was governed by the Navier–Stokes equations and continuity equation. Mass transfer within the blood lumen and through the arterial wall was coupled with the blood flow and modelled by the convection–diffusion equation. Kedem–Katchalsky equations described low-density lipoprotein (LDL) transport in lumen of the vessel. Two time periods were considered (baseline and follow-up). The results of the analyzes have shown that zones with lower shear stress values were correlated with the zones of plaque accumulation and progression. This was confirmed at the follow-up, where simulation results had shown that carotid lumen was reduced due to plaque progression. This type of numerical simulations has become significant support to medicine, due to capability to determine the zone of plaque appearance and predict its further progression.

This paper presents a novel method for processing heart sound signal for screening forth heart sound (S4). The proposed method is based on time growing neural network with a new scheme, which we call the Backward Time-Growing Neural Network (BTGNN). The BTGNN is trained for detecting S4 in recordings of heart sound signal. In total, 83 children patients, referred to a children University hospital, participated in the study. The collected signals are composed of the subjects with and without S4 for training and testing the method. Performance of the method is evaluated using the Leave-One-Out and the repeated random sub sampling methods. The accuracy/sensitivity of the method is estimated to be 88.3%/82.4% and the structural risk is calculated to be 18.3% using repeated random sub sampling and the A-Test methods, respectively.

The study of microbiome and its relationship with the host organism has recorded rapid increase in popularity over the past decade. The advances in the sequencing techniques used for extraction of microbiome data have stimulated the development of sophisticated bioinformatics tools used to analyze large amounts of data. The gut microbiome, as a network of microorganisms that is the focus of this study, has been implicated in several disorders such as colorectal cancer, obesity, irritable bowel syndrome, diabetes, and metabolic syndrome, and more recently in the study of Parkinsons and Alzheimers diseases as well. This study aims to examine the relationship between multiple sclerosis, autoimmune central nervous system disease, and gut microbial community composition, using the samples obtained 16s rRNA sequencing technique. Healthy control and multiple sclerosis groups of sequences were analyzed. Using the extracted set of statistically significant bacteria, a Random Forest classifier has been developed. The most significant microbiome alterations in multiple sclerosis patients imply increase in Akkermansia and Methanobrevibacter, and decrease in Butyvricimonas bacteria at the genus. The highest accuracy scores obtained by the developed classifier are 84.61% using the genus level bacteria. The presented methods and results define a paradigm that can be used to help guide medical decision making.

In previously in vitro studies on different cell lines and in vivo on melanoma and 4T1 murine breast cancer and metastasis it was shown antiproliferative activity for ester derivatives of (S,S)-ethylenediamine-N,N′-di-2-(3-cyclohexyl)propanoic acid, and (S,S)-1,3-propanediamine-N,N′-di-2-(3-cyclohexyl)propanoic acid. The aim of this study was to predict membrane permeability by parallel artificial membrane permeability assay (PAMPA), molecular mechanism of action, metabolites and absorption, distribution, metabolism, toxicity—ADMET properties for observed substances using in vitro and in silico methods. Obtained results of PAMPA show the best membrane permeability of ethyl esters analogs (DE-EDCP and DE-PDCP) and refer to the hypothesis that the retention in cell membrane is important for cytotoxic activity of investigated substances. Prediction of main metabolic pathways was performed by the Metabolizer software and it was obtained that the major metabolic reactions were the hydrolyses of ester and subsequently intramolecular cyclization. Toxicity of investigated substances and their potential metabolites are lower than toxicity of observed official cytotoxic drugs. Based on the results obtained by the Molecular docking, it can be assumed that the antiproliferative effects of the investigated substances were realized through the multiple mechanisms by potential metabolites: acids, lactam carboxylate and lactam alkyl esters, while the esters are probably a prodrug substance with favorable properties to provide sufficient bioavailability at the target of action. Based on obtained results it can be proposed there to be investigated the existence of the metabolites: lactam carboxylate and lactam alkyl esters in biological materials.

Autism Spectrum Disorder (ASD) is a broad spectrum of disorders which manifests itself through number of different phenotypes including those affecting communication and behavior. Our aim was to investigate small non coding RNA molecules, miRNAs, and their effect on target genes involved in neurodevelopment and ASD. In addition, we performed our study by investigating selected miRNAs as potential biomarkers for diagnosing children with ASD. MiRNAs selected for this study are found in saliva samples; therefore, sampling is non-invasive and very attractive diagnostic tool for ASD. Children diagnosed at an early stage of life would have the most benefit from an early intervention. We have identified 7 target genes of miRNAs suspected to be involved in ASD through an in silico analysis. We have found negative regulatory interactions between differentially expressed miRNAs and putative targets in ASD. The seven genes found through this study are all connected to neurodevelopmental functions and processes. Malfunction of some or all of these genes is found in connection to ASD and/or other neurodevelopmental disorders. The following 7 genes were found as best candidate genes of miRNAs studied: MAPK10, KCNMA1, DST, ZBTB20, GAS7, NTRK2 and SCN2A.

Since the main purpose of generation of organ-on-chips is to reduce and, at some point, replace experiments on the animals, several different organs were point of interest in developing on-chip technology. The paper will therefore focus on creating mathematical model of liver cell aggregation, generating a basis for creation of artificial organs in that way. Some studies have shown that in the case of hepatocytes (liver cells), improved cell viability and functionality is connected to the formation of spheroidal multicellular aggregates in comparison to the traditional monolayer culture techniques. We present one-dimensional mathematical model of liver cell aggregation, meaning how the liver cell clusters are formed on an extracellular matrix (ECM) layer. Model is based on partial differential equations in the function of space and time, which are solved numerically using finite difference method. Results show that velocity of the cells at the beginning is slow, only to increase later on during the formation of the aggregates. Material properties and initial cell seeding have great effects on the formation of the aggregates. With this model, we aim to achieve a prediction of number of cell clusters, velocity during and before/after clustering etc., which is important in experiments to examine how different parameters, such as initial cell seeding or material characteristics affect cell aggregation and viability of liver cells.

The ultimate goal of smart things and systems should be to improve Quality of Life (QoL), specially of elderly given that population is increasing rapidly. A number of smart ageing solutions are developed without QoL of elderly being noticeably improved. This paper seeks to answer the question are the existing smart ageing solutions succeeding in direct improvement of QoL of elderly. After conducting a survey study for this purpose, the results showed that existing solutions are not succeeding in improving QoL of elderly. In addition to this conclusion, the contribution of this paper reflects in proposed set of QoL indicators for elderly and recommendations for future research activities in this area.

This research focuses on detecting psychiatric disorders in adults by applying a Turkish text analysis system. The study examined pre-diagnosed depression, mania and healthy adults. The distinct words and their categories of the subjects’ text data along with their existence, frequency or weighted values were used as the features of the ML techniques Naïve Bayes, Bayesian Logistic Regression and Support Vector Classifier. The promising results of the study, some of which were above 80%, show that language usage can be a good indicator of psychological states of the subjects. The goal of the study is to obtain the semantic ontology and dictionaries specific to various disorders and to develop a new digital mental health system infrastructure as a mobile software that will facilitate the diagnosis of psychiatric disorders and patient follow-up by using computerized content analysis of the big and dynamic communication texts. It will provide means to produce short- and long-term strategies in the health sector by fulfilling the needs in the fastest, the most proper and the most efficient manner.

Recent requests for international assistance regarding clinical engineering (CE) registration/certification and related legislation resulted in a survey for the International Federation for Medical and Biological Engineering (IFMBE) leadership. The survey comprising two questions (‘What is CE?’ and ‘How can we advance CE globally?’) with five sub-questions each, was e-mailed to 63 members and collaborators of the Clinical Engineering Division of the IFMBE (CED/IFMBE) and to 16 members and collaborators of the Health Technology Assessment Division of the IFMBE (HTAD/IFMBE). The survey response rate was 34%. All respondents were of the view that CE is not synonymous with either biomedical engineering (BME) or health technology management (HTM). Significant affirmative responses included: ‘CE is a subset of BME’ (89% of respondents); ‘CE encompasses HTM’ (73%); ‘CE practitioners are health professionals’ (93%) and ‘CE is not only for engineers’ (74%). Other responses were as follows: ‘Do/can we legislate?’ (41% of respondents), ‘Do we register?’ (74%), ‘Do we certify?’ (83%) and ‘Do we support accredited CE undergraduate programs?’ (89%). Survey results should assist both CED/IFMBE leadership and other global stakeholders in defining concrete practical steps to advance formal recognition of CE practitioners.

This paper presents a custom decision-support information system designed to analyze and manage healthcare buildings, estate and assets in relation to the activity area of each room. The software drives its own SVG plans to retrieve structural information with a room-scale definition, built by DXF files inputted to the system itself. Each room is grouped in homogeneous areas according to the hospital’s inner organization (Departments and Operative Units) with their own assets, technologies and environmental comforts, giving quantitative and qualitative results. The system output can be used by the top-management to assess parameters and improve the structure and organization.

The paper presents a system for managing and monitoring environmental parameters in hospital facilities. It relies on existing data collected with a CAFM (Computer Aided Facility Management) system and allows granted users (such as CEO or Energy Manager) to monitor the ongoing energy consumption of a given activity area (Operating Rooms, Diagnostics, Intensive Care Units, Wards) in relation to the compliance to relevant threshold parameters. The system easily outputs aggregated data via PDF reporting.

The Adverse Drug Events (ADEs) can be defined as errors in therapy that are not desirable, not intentional and foreseeable, that can cause or lead to an inappropriate use of the medication or to a danger for the patient. In this work it is shown the design, engineering and realization of a prototype device for the safe and secure administration of pharmacological therapy using RFID. In particular, the redesign of the prototype antenna is addressed, with a focus on its enhanced performance.

Most of the world population is being treated in low-income countries, where there are not only harsh environmental conditions but also a failure to meet international standards and minimum requirements of the medical devices and locations. This can jeopardize the safe and efficient functioning of the medical devices. This paper draws on 5 field studies that took place in Sub-Saharan Africa, presenting few examples of donated medical devices and discussing the possible steps in order to strive for a more universal free healthcare coverage.

This paper presents a unique software tool, eVerlab, for the management of medical device (MD) safety and performance inspection in healthcare institutions that are part of the Legal Metrology Framework. This is an online application, a functional tool for laboratory staff that perform MD inspections and for healthcare institutions staff enabling efficient management of MDs. It is composed of a Graphic User Interface (GUI) with the application of enabling the user to access its database. The software’s database has imported records of real-time measurement measuring data which users have immediate access to. It creates the opportunity of users to review performance statuses of all medical devices in healthcare institutions. From the beginning of its application until today, the number of healthcare institutions registered in eVerlab and the number of verifications has significantly increased. Today, eVerlab software solution has 218 registered clients comprising over 3000 inspection reports of medical devices operating in Bosnia and Herzegovina. The database of the software solution provides the information necessary for a detailed analysis of performance variation, based on the historical behavior of different medical devices. The data collected and stored into the database can be used as input data to Machine Learning Algorithms for developing automated systems for the prediction of MD performances.

Hearing devices in many different brands and types are used in our country. However, these hearing aids before being placed on the market do not pass mandatory/legal technical measurements. To verify that hearing aids work in a specified performance, measurements are always required to be done on the basis of scientific parameters and standards. For this purpose, the acoustic cabinet, microphone, ear simulator, analyzer and software-aided system was established in TÜBİTAK UME Medical Metrology Laboratory. The acoustic field generated by the sound source within the acoustic cabinet is analyzed with the reference microphone and ear simulator. In this set-up system, performance parameters such as acoustic impedance measurements in the range of between 100 Hz and 10 kHz, sensitivity, frequency response and noise insulation value are measured. In this paper, performance parameters’ measurements of the sound pressure level of headphones that are designed specifically for musicians in Turkey are presented in 2.0 dB uncertainty.

Medical device calibration and test are one of the emerging, important and critical issues in the field of metrology. The traceability in medical devices and measurements are not powerful enough as much as the traceability in technical and military calibration and measurements. Patient safety is a must for the medical device industry and applications in the health sector. Therefore all measurement devices used in the medical field must be controlled periodically and all measurements must be standardized as a quality control regimen that guarantees the reliability of medical devices. Test, measurement, and calibration of bio-medical equipment are becoming increasingly significant for manufacturers when accuracy in diagnosis and effectiveness in treatment are required as well as patient safety. For this reason, it is expected that this article will provide a clear approximation of the correct measurements in the medical field as a guide to medical metrology studies.

The subjectivity and the multidimensionality of pain raises several challenges in terms of its description, assessment and treatment. This study presents a Clinical Decision Support System for the pain condition based on the fusion of its different dimensions in order to produce an accurate and reliable assessment. The proposed system includes not only the value of the pain intensity but also several scores (e.g. regarding anxiety, or depression) obtained from the analysis of patients’ behaviour related with the posted messages on social networks, such as Facebook, or Twitter. This study aims to introduce the paradigm for the pain assessment based on patients’ behavioural scores to the detriment of it self-reporting of pain.

The paper aims to apply a decision tree based machine learning algorithm to predict possible alcohol addicts among high school students. The data mining process is performed on the real-world data collected in two high schools in Portugal. The dataset is originally designed for the estimation of high school student’s performance where alcohol consumption is used as one of the parameters. In the implementation phase, KNIME analytics platform is applied to test the model. The significant part represents preprocessing of data where the new attributes are derived including class attribute labeled using alcohol addict matrix. Afterwards, the linear correlation is used to reduce the number of features. Data processing consists of dividing the dataset into training and test data, making artificial data for training phase and lastly analyzing the outputs of decision tree learner and predictor. Constructed decision tree determines the connections between certain attributes and student alcohol consumption. Finally, the overall accuracy of the model is measured using a confusion matrix.

The neural activity of the brain may be observed by means of an electroencephalogram (EEG) whose analysis and/or interpretation may lead to the recognition of human activities and behaviors. However, on imagined body movements the brain produces the same EEG patterns as the action performed. This study aims to differentiate real movements from imagined ones, through EEG signals. Three different models; Support Vector Machine, Logistic Regression, and K-Nearest neighbour were implemented to classify these events. The preliminary results, obtained from 15 participants, revealed that the Logistic Regression was the best classifier into the proposed model with accuracy rates varying from 36.8 to 90%. Finally, complementary studies should be addressed to optimize not only the accuracy but also to assure uniform accuracy among the different participants.

The thyroid gland is one of the largest endocrine glands in the body and excretes two major hormones: thyroxine and triiodothyronine, known as T4 and T3, as well as calcitonin, a hormone important in calcium metabolism. Thyroid hormones are secerned into the bloodstream and are transported to every tissue in the body where they help energy utilization, maintain heat and regulate brain, heart, muscle function and functions of other organs. Primarily, the thyroid gland secretion is controlled by the thyroid stimulating hormone (TSH), secreted from the adenohypophysis. Increased hormone blood levels represent the hyperfunction of the gland or hyperthyroidism, and hormone deficiency is considered as a condition of hypofunction or hypothyroidism. An application has been developed based on an algorithm, and is used to determine the thyroid gland dysfunction. HypoTir application is based on the following parameters: TSH, fT4, T3 concentration, and presence of thyroid gland antibodies. The diagnostic performance of the application depends solely on the accuracy of the applied algorithm. For specific parameter values application displays a possible diagnosis. Further work and computational development in medicine is needed to provide faster, better and more efficient care as well as patient awareness and knowledge on existing illnesses.

This paper presents development of Expert System for prediction of performance of infant incubators based on real-time measured data. Temperature error, preventive maintenance intervals, number of additional parts and utilization coefficient were used as input information for the development of this system. Expert system is based on Artificial Neural Network (ANN) and Fuzzy logic (FL) classifier. Feed forward back-propagation artificial neural network with 12 neurons in hidden layer and sigmoid transfer function, using Bayesian regulation algorithm has shown best properties for prediction of the functionality of incubators based on performance output error. Fuzzy logic using Mamdani implication logic was developed as an extension of ANN and finally used for prediction of device performance. The developed expert system presented in this paper presents the first step in researching possibilities of usage such systems for upgrading medical device management strategies in healthcare institutions to answer challenges of increased sophistication of devices, but patient safety demands as well.

Heart disease is the one of the most serious problems in healthcare and affects large number of people. It is very important to detect it on time, otherwise it can cause serious consequences, such as death. In this paper, we applied artificial neural network, k-nearest neighbor and support vector machine algorithms to build model which will be used for prediction of heart disease. Multiple experiments using each of these algorithms are performed. Additionally, the ensemble learning is applied, and results are compared. Initially, the problem was approached as multiclass classification, however it was transformed into the binary classification problem, to simplify model since number of outputs is reduced from five to two. In both cases, the highest accuracies are obtained by majority voting which are 61.16% for multiclass classification and 87.37% for binary classification.

Artificial intelligence methods offer a modern approach in solving different problems in the field of pharmacy, especially in the area of pharmaceutical technology. The main goal of this article is to present artificial intelligence methods that facilitate granulation and tableting processes. Artificial intelligence methods with the major impact in this area include artificial neural networks (ANN), cubist model, random forest method, k-NN and the combination of neuro-fuzzy logic (NFL) and gene expression programming (GEP). Besides giving a brief introduction to the methods listed above, the scientific goal of this paper is to present the on-going use they have in wet granulation process, roll compaction, solving the capping problems of the tablets, as well as helping with the scale-up process and quality improvement of ramipril tablets. In time to come, it is assumed that the diversity and pliability of the artificial intelligence methods can advance in the tablet making process, ensuring the much needed support in data analyzing and solving complex problems of tablet manufacturing that contain various input and output specification. It should always be duly noted, that even though artificial intelligence methods are far superior to the human brain when it comes to problem-solving and multitasking, these methods, and computer programming can never be the head of the operation, they could only mimic that.

An Artificial Neural Network for lactose intolerance prediction is presented in this paper. The system input information were symptom related questions and answers from a condition-oriented questionnaire, that was filled by one hundred individuals from Bosnia and Herzegovina. Participants were genotyped on LCT 13910 C/T and LCT 22018 G/A polymorphisms, which are reliable predictors of lactose tolerance/intolerance, and that information was the output of the neural network. The ANN consisted of 6 input parameters, that feed the Bayesian regulation training algorithm with information. ANN performance evaluation was performed with 10 samples out of 100 genotyped samples and the results predict whether a person is lactose tolerant or lactose intolerant. The aim of the artificial neural network presented in this paper is to assist specialists in lactose intolerance prediction, avoiding unnecessary further laboratory and genetic testing in clinical practice.

Diagnosing ovarian cancer is a medical challenge to clinical researchers. This study aims to develop a novel prototype of clinical management in diagnosis and management of patients with ovarian cancer. Various classification algorithms can be applied to cancer databases to devise methods that can predict cancer manifestation. Various methods, however, vary in terms of the level of accuracy, depending on the classification algorithm used. Identifying the most accurate classification algorithm is a challenging task, primarily due to limited data availability. In this paper, a comprehensive comparative analysis of nine different classification algorithms was conducted and their performances have been evaluated. The results indicate that all classifiers are relatively equal in accuracy, meaning that multiple classifying techniques can be used to support physicians in rendering more informed diagnostic decisions.

In almost all parts of the world, breast cancer is one of the major causes of death among women. But at the same time, it is one of the most curable cancers if it is diagnosed at early stage. This paper tries to find a model that diagnose and classify breast cancer with high accuracy and help to both patients and doctors in the future. Here we develop a model using Normalized Multi Layer Perceptron Neural Network to classify breast cancer with high accuracy. The results achieved is very good (accuracy is 99.27%). It is very promising result compared to previous researches where Artificial Neural Networks were used. As benchmark test, Breast Cancer Wisconsin (Original) was used.

The detoxification mechanisms occurring in the cells and tissues of the body are necessary to maintain homeostasis. The CYP enzymes family support these mechanisms, take a part in the pharmacokinetics of drugs and neutralizing xenobiotics. The predominant sub-family of CYP enzymes are CYP3A5 coded by gene CYP3A5. The distribution of CYP3A5 variants varies in different ethnic groups, while the absence of functional CYP3A5, linked to diminished enzymatic function, is most frequent. Knowledge about distribution of CYP3A5 variants in different ethnic groups is important to establish the clinical relevance of screening for these variants and to optimize and individualize pharmacotherapy. The aim of the study was to establish the distribution of variants *1 and *3 of CYP3A5 gene and compare our results with those from other Central-Eastern and South European populations. The studied population consisted of 469 healthy adults: Belarusians, Bosnians and Poles (241 female and 228 male) mean age 50.68 (±16.09) y. DNA was extracted from buccal swabs, and for the *1 and*3 variants of CYP3A5 gene, the PCR-RFLP was performed. The frequency of the CYP3A5*3 variant in Belarussians, Bosnians and Poles was 98.44, 97.89 and 94.56%, followed by the *1 variant: 1.56, 2.11 and 5.44%, respectively. We showed that Central-Eastern and South European populations are characterized by high variability of CYP3A5 variants. This may be taken into consideration in the prognosis of pharmacotherapy efficacy in the studied populations.

There is considerable potential for pulmonary gene therapy as a treatment for a number of conditions for which current treatment is inadequate. Delivering genes directly to the lungs by dry powder inhalers (DPIs) have attracted much attention due to better stability of genes. Formulating genes as powders for aerosol delivery is a challenge as it requires not only flowability and dispersibility of the powders but also maintaining gene stability and biological activity during manufacturing and delivery. In this review, we aim to provide an overview about the potentials of spray-freeze-drying (SFD) for the development of inhalable dry gene powders for pulmonary drug delivery. We will discuss the main steps involved within the production process (i.e., spraying, freezing and drying) and introduce different SFD methods which can successfully be used for the production of porous particles whose physical and aerosol characteristics are considered to be ideal for use in pulmonary drug delivery.

The aim of this study was to examine the antimicrobial activity of selected wild mushrooms from different areas of Bosnia traditionally used in the diet. These are the first tests of antimicrobial activity of fungi extracts growing in Bosnia and Herzegovina. Wild mushrooms Boletus edulis Bull. (1782) and Cantharellus cibarius Fr. (1821) were collected from different areas of Bosnia and Herzegovina. Nine microbial strains were tested: four Gram-positive bacteria (Staphylococcus aureus ATCC 25923; Methicillin-resistant Staphylococcus aureus: MRSA ATCC 33591; Bacillus subtilis ATCC 6633; and Enterococcus faecalis ATCC 29212), four Gram-negative bacteria (Salmonella abony ATCC 6017; Pseudomonas aeruginosa ATCC 9027; Escherichia coli ATCC 25922; Extended Spectrum Beta-Lactamase producing E. coli: ESBL E. coli ATCC 35218), and one yeast Candida albicans ATCC 1023, through the agar well diffusion method. Investigated wild mushrooms performed antibacterial activity against three strains of Gram-positive bacteria: S. aureus, MRSA and B. subtilis. Antibacterial activity of the examined extract depends on the locality on which mushrooms grow. The broader spectrum of antibacterial activity was observed in case of C. cibarius extracts, and largest inhibition zones with this mushroom species were recorded against S. aureus (18.11 ± 0.20 mm) and B. subtilis (18.10 ± 0.17 mm). Extracts of B. edulis exhibited the largest inhibition zones against MRSA (20.03 ± 0.08 mm). In comparison to the standard antibiotic, tested extracts showed significant inhibition of this multidrug-resistant pathogen.

This paper presents the redox properties of hypothyroid drug L-thyroxine without and in the presence of sodium pertechnetate (99mTc) by an electrochemical method on glassy-carbon (GC) electrodes using a cyclic voltammetry technique. The cyclic voltammetry method was used to investigate the effects of various concentrations of L-thyroxine without and in the presence of 99mTc radiopharmaceuticals, the effect of the number of scan cycles, as well as the effect of 99mTc activity on the appearance of cyclic voltammograms. The results show that with the increase of the concentration of L-thyroxine, the increase of the peak current in the reduction area is notable. Obtained results show that the application of different concentrations of 99mTc on the drug exhibits the inhibitory properties of used radiopharmaceutical in the treatment of hypothyroidism.

A novel system of delivery presents many advantages such as sustained delivery, higher bioavailability, improved medication compliance, and therapeutic outcomes, patient monitoring, and minor side effects. One of the improved ways of drug delivery is electronic capsules which can deliver drugs to a specific site in the gastrointestinal tract and can also be used for patient monitoring. Wireless transdermal patches are a novel electronic drug delivery system, which is portable, disposable and worn on the skin surface to deliver medications on the transdermal level. Electronic transdermal drug delivery has made a major contribution to clinical practice due to improving the efficiency of drug delivery over the conventional route. The improvement can provide a solution for getting rid of the bondage of batteries as well as the restrictions of inconvenient wires, on self-powered systems. The greatest achievement of wireless transdermal patches is the ability to further improve transdermal drug delivery for certain drugs that could not be administered using conventional transdermal patches. Electronic drug delivery systems such as capsules, on the other side, can be used not only to deliver drugs to a specific site in the gastrointestinal tract but can also record data and report the state of patients gastrointestinal tract, and after excretion, this information can be studied and used to present them graphically.

UV/Vis spectroscopy is usually used in identification of active substances in drugs. The aim of this study was to test the application of the derivative UV/Vis spectroscopy in determination of the active substances content (ASC) in some drugs. Acetylsalicylic acid (ASA), meloxicam (M) and naproxen (N) were the selected ASC that were analyzed in different drug samples. The all analyses were carried out on the Perkin-Elmer Lambda 25 spectrophotometer in triplicate. The pure ASA, M and N were used as standards, and the calibration curve method was used to determine the ASC in the samples. The absorption spectrums were recorded in the visible (Vis) region 400–800 nm for ASA, and in ultraviolet (UV) 200–400 nm region for M and N. After recording the absorption spectrums, a third-order derivations were made using UV WinLab software. The obtained ASC was within acceptable limits with declared values (d.v.) for the two drugs: [meloxicam in Melox (Nobel), and naproxen in Nalgesin S (Krka)]. The observed deviations were <10% (the measured meloxicam content was 92.27%, and for naproxen was 90.06%) of the d.v., which is in line with the U.S. Pharmacopoeia (U.S.Ph.). In the case of Aspirin protect 100 (Bayer), the content of ASA was 89.56% of the d.v., which is slightly lower than that prescribed by the U.S.Ph. (deviation ±5% of the d.v.). Based on the obtained results, it can be concluded that UV/Vis derivative spectroscopy is a suitable method for determining of the ASC in some drugs.

Capsaicin has been applied topically to treat some peripheral painful states, such as rheumatoid arthritis, cancer pain and diabetic neuropathy. Due to the pre-systemic metabolism of intragastric capsaicin and very rapid elimination half-life made topical application of capsaicin advantageous. The aim of this study was to evaluate differences in the dissolution characteristics of capsaicin transdermal patches commercially available on the local market (formulation I, II and III). USP Apparatus 5 (Paddle Over Disc) is used for transdermal patch release testing at fixed rotation speed (50 rpm). The 9 cm2 patch was exposed to 500 mL of phosphate buffer solution pH 4.0, 5.0 and 7.4. All dissolution studies were carried out at 32 ± 0.5 °C and samples were collected at various time intervals (60, 240, 480 and 720 min) and analyzed for capsaicin content using optimized and validated high-performance liquid chromatography (HPLC). The mobile phase consisted of acetonitrile:water (50:50 v/v). pH change in the release media showed no significant difference in capsaicin release profile for formulation I and II. For formulation III, the resulting results vary considerably with pH change. Although several apparatus and procedures have been used to study in vitro release characteristics of transdermal patches, USP Apparatus 5 could be considered as a discriminatory test that would be able to detect the differences in the dissolution rate of all tested capsaicin patches at short sampling intervals (1–12 h).

Acetylsalicylic acid is the salicylic drug which is commonly used like analgesic, antipyretic and anti-inflammatory drug. There are a lot of methods for analysis, but we decided for UV-VIS spectroscopy. In this paper are correlation results from UV-VIS determination of acetylsalicylic acid in six aspirin tablets from different manufacturers in Bosnia and Herzegovina using two different methods and changing parameters in first one. Standards and samples are prepared at the same way. First method was done using 1 M NaOH for degradation of acetylsalicylic acid and development of colors with 0.02 M FeCl3 in 0.03 HCl (optimal pH = 1.6). For this analysis we made (multiple times) five standards with different concentrations (50–250%), changing pH of FeCl3/HCl solution (0.60, 1.60, 1.95). Then, we changed the concentration range of standards: 50–250, 80–120, 80–160%. The best absorbance results were at 530 nm using FeCl3/HCl solution at pH 1.60, so we analyze samples using that solutions. The second method was dissolving standards and samples in concentrated ethanol and measuring absorbance at 227 nm. Both method gave good results and can be used for pharmaceutical research.

Introduction: Enzybiotics are enzymes with antimicrobial and immunomodulatory activity. The aim of this study was to investigate the effectiveness and safety of enzybiotic lysozyme in combination with pyridoxine for the prevention and treatment of postoperative complications after bilateral tonsillectomy. Materials and Methods: The study was designed as randomized controlled, parallel-group, open, prospective, multicenter clinical study in adult patients after bilateral tonsillectomy. 160 patients were randomized to the lysozyme + pyridoxine or control group. Efficacy was evaluated by: Visual analog scale (for pain), clinical signs (for wound healing and postoperative complications), and the need for treatment (with analgesics and systemic antimicrobials). Safety was evaluated by reporting adverse effects. Results: Lysozyme + pyridoxine was superior to control with respect to the pain reduction (starting already from the first day of treatment), the reduction of local fibrin deposits and the need for analgesics. No statistically significant difference was seen regarding local bleeding (less than 15% patients in both groups) and infection (less than 5% patients in both groups). Systemic antibiotics were used by 16 patients (19.1%) in lysozyme + pyridoxine group and 24 patients (31.6%) in control group (no statistical difference, P > 0.050). Conclusion: Lysozyme + pyridoxine showed beneficial effects in respect of suppression of pain with subsequent lower need for analgesics, as well as in the faster process of healing of postoperative scar. Moreover, next to its suitability for application, lysozyme + pyridoxine lozenges showed excellent tolerability and safety profile.

Use of microneedles as drug delivery systems provides a number of benefits to patients. Easier and simple drug use, reduced side effects, and incontinence are some of them. Microstock patch has been developing for the last few decades and they represent minimally invasive way for administration drugs in organism through the skin (transdermal administration). One of the approaches ‘‘poke with patch’’ uses microneedles to make holes (Hollow microneedles) and then apply a transdermal (TD) patch to the skin surface. TD drug delivery can improve compliance, minimize peaks, provide continuous drug administration and troughs in plasma levels during the day. These systems can take the place of more risky and invasive injection-based drug delivery (such as insulin injection). Objective of this paper is to research and present the application of hollow microneedles in treating diabetes and to compare it with conventional application of the drug. The drugs that we processed are metformin, insulin and exendin. Metformin is effective for treating diabetic patients therapeutically and preventively, maximizing the use of the current diabetes patch device. The main lack of conventional application of insulin is the fact that the application itself isn’t optimal for a patient. TDl showed significant improvement at level of absorption and bioavailability of the drug. New findings indicate that Exendin-4 diabetes microneedles can potentially replace the currently used subcutaneous (SC) injections because they can effectively reduce blood-glucose levels in patients with type 2 diabetes and are convenient to use.

Azo compounds represent about two thirds of all synthetic dyes. Their usage in pharmaceutical industry has many purposes. One of the most important is coloring of pharmaceutical agents which improves their easy identification. Azo dyes often used in manufacturing of pharmaceuticals are: E102 Tartrazine, E110 Sunset Yellow FCF, Ponceau 4R (Cochineal Red A), Azorubine (Carmoisine), Amaranth, E133 Brilliant Blue and E129 Allura Red. Many azo dyes show carcinogenic and mutagenic activity, and they can provoke allergic reactions. Generally, toxicity of ingredients grows with the increase of benzene rings in their structure. Carcinogenicity of azo dyes directly depends on the structure of molecule and on mechanism of degradation. Products of degradation of azo dyes are mostly aromatic amines with different structures and they can also have carcinogenic properties. Carcinogenicity of many azo dyes is due to their cleaved products such as benzidine. Benzidine is known as carcinogen for the human urinary bladder. Except of carcinogenic and mutagenic activity, azo dyes can alter biochemical markers and they can provoke allergic reactions.

Type 2 diabetes mellitus (T2D) is a complex metabolic disorder associated with disturbances not only in carbohydrates and proteins but also with impairment of lipid metabolism. It is largely influenced by complex interactions of environmental and genetic factors, or both. High prevalence and increasing number of patients with T2D in the world, represent constant challenge for better elucidation of pathophysiological processes that lead to development of disease. In this paper, I have tried to summarize the results of my research and new findings from recent analyses of genome-wide association studies (GWAS) which helped us in the identification of common and rare genetic variants associated with insulin resistance (IR), dyslipidemia, Metabolic syndrome (MetS) and Type 2 diabetes. Many variants of certain genes are directly involved in glucose metabolism; however, functional and additional studies are suggested in order to be able to understand the contribution of other variants associated with impaired lipid and lipoprotein metabolism. New technologies such as metabolomics, proteomics, genomics, a more recently, lipidomics clearly point out directions in identification and detection of good/best biological gene candidates involved in fatty acid and lipoprotein metabolism. Mutational sequencing for these genes i.e. genetic regions associated with T2D, obesity, dyslipidemia and IR, could serve as a protective measure for not only insulin sensitivity but also, insulin secretion, obesity and other glycemic traits.

Chromosomal aberrations are a hallmark of leukemia. The prognostication of acute lymphocytic leukemia (ALL), chronic lymphocytic leukemia (CLL), acute myeloid leukemia (AML), and chronic myeloid leukemia (CML) has vastly expanded with chromosomal analyses over the years. Current treatment strategy has been refined by discovery of genes and its mutations which are involved in disease causation and progression. These genes are named biomarkers or prognostic markers and they give information about favorable and unfavorable prognosis of the patients. This paper aims to summarize the most common mutated genes in all four types of leukemia and to find correlation of their expression and point mutations in certain tissues, using COSMIC database. Highest number of point mutations in leukemia genes was found in hematopoietic and lymphoid tissues and it was three times higher than in other tissues which could be explained by relatedness of genes with specific leukemia. Mostly overexpressed gene was CEBPA whereas NOTCH1 gene had the highest number of point mutations. Further research about new prognostic markers is crucial because they can significantly improve development of new therapeutic targets thereby increasing patient outcome and quality of life.

The human skull shows certain morphological differences between male and female that can be used in the sex determination of skeletal remains. One of these differences is in the size and shape of the foramen magnum, which is important for sex determination especially in burned cadavers because the area around the foramen magnum is covered by a greater amount of soft tissue which protects bones. The aims of this study were to determine the prediction of sex determination based on craniometric analysis of foramen magnum of the human skulls. Material and method: The research was conducted on 100 human degreased and macerated adult skulls of known sex and known age (50 male skulls, 50 female skulls) selected by randomization of 211 human skulls (139 male and 72 female skulls) belonging to the Osteological Collection of the Department of Anatomy, Medical Faculty, University of Sarajevo. For analysis of the size of foramen magnum we used the craniometric method where we measured two linear diameters of foramen magnum and where we calculated the area of foramen magnum using two formulas published by Radinsky and Teixeira which are based on the sagittal and transverse diameter. Results: ROC curve revealed that the predictability of sagittal diameter of foramen magnum in sex determination of skull was 73%, the predictability of transverse diameter of foramen magnum in sex determination of skull was 65.3%, and the predictability of area of foramen magnum in sex determination of skull was 70.9% when this area is calculated using Radinsky formula, and 71.2% when this area is calculated using Teixeira formula. Conclusion: All diameters of the foramen magnum and area of the foramen magnum showed sexual dimorphism. Sagittal diameter showed the hightest effect for gender determination (73%), followed by area (FM ≈ 71%) and the least effect was shown by transverse diameter with 65.3% accuracy.

Various chemical agents or pharmaceuticals as drugs administered into the body in increased concentrations for a long time may have hepatotoxic or carcinogenic effect. In human biomonitoring are used different biomarkers, which can confirm the presence of various chemical agents in the body and their effects on cells or molecules. The aim of the study is to biomonitoring of the hepatotoxic effects of statins (atorvastatin and rosuvastatin) as a chemical agents or drugs in therapy of patients with dyslipidemia, using biochemical biomarkers as liver enzymes. Materials and methods: Follow-up laboratory tests (AST, ALT, GGT, ALP, cholesterol, and triglycerides) were evaluated with biochemical analyzer Cobas Integra 400 Plus, after 6 months of treatment with statins. The study included 28 subjects, aged 28–84 years (the mean 63.7), 15 women and 13 men, mainly patients with confirm dyslipidemia. Results: The observation of total serum transferases confirmed that 20 of the subjects (71.42%) have a normal serum transferases (AST and ALT) but 8 of the subjects (28.58%) (Groups 1 and 2) have a abnormal level of serum transferases. Subjects in Group 1 (5 subjects with atorvastatin therapy) have an abnormal level of serum transferases (AST and ALT), the mean value of AST was 43.6 U/L and for ALT 73.6 U/L. Subject in Group 2 (3 subjects with rosuvastatin therapy) has >10 times more of the level of AST and ALT (the mean value of AST was 580.3 U/L, and ALT 1802.3 U/L). In the Group 2 we reported older patients (with the ages after 60) with long time therapy with rosuvastatin (more than 6 months) who demonstrated significant elevation of ALT according with other chronical diseases as a cardiovascular diseases, diabetes mellitus type 2, acute pancreatitis and in alcohol abusers. Conclusions: We want to emphasize the importance of biomonitoring of liver enzymes as biomarkers which associates hepatotoxicity. Statins therapy (on patients with dyslipidemia) combined with other metabolic drugs and inhibitors, might increase the risk of liver injury. Individual differences, such as sex, age, sensitivity and immune ability, affect the degree of hepatotoxicity of various drugs (in our study statins) as a chemical agents present in the body.

Antibiotic resistance is a live issue when it comes to public health and emerging infectious diseases. Opinion of many experts in this field is that misuse or overuse of antibiotics have contributed to fast development of antibiotic resistance. This paper is focused on genetics alterations of bacteria caused by misuse of antibiotics. The acquisition of resistance can occur by horizontal or vertical transmission, so we described the mechanisms of resistance, as well as evolution of resistance genes. We explained mutagenesis induced by antibiotics, as well as recombination and lateral transfer mechanisms. At the end we got to multiple drug resistant bacteria, as a most urgent threat to a public health. Many strains of bacteria become resistant, or in many cases multi-resistant to many therapeutic drugs because of their ability to adapt to the environment and to develop different mechanisms of resistance to most old and new antimicrobial agents. Some strains have become resistant to practically all of the commonly available agents.

The main scientific goal of this paper is that on the basis of the collected photos, files and documents, we can make one large database that will help us successfully in future use in medical sciences (dermatology), for early detection and diagnosis of the patient’s disease. In this research, we used techniques for fingerprint recognition. These techniques can be divided into three phases, pre-processing, extraction of minutiae and comparison of minutiae. Based on the theoretical expose that has been written and MATLAB code that performs all of these actions. With the help of MATLAB code we were able to make a comparison with the desired image of a fingerprint and get to know whether the test person has any of these skin diseases.

Purpose: Cancer may have several pathways of formation, including changes in genes. Thus, this article points out the genes related to specific and nonspecific types of tumors, as well as the importance of this data for the health care area. Methodology: This is a Literature Review made from the PubMed database. The research randomly used 200 articles from 2013 to 2018 with the keywords “epigenetics” and “cancer”, of which only 24 were selected since the others did not present the description of the gene related to the tumor. Results: 25 articles were selected, most of them focused on hepatocellular carcinoma. Among the tumors derived from systems, those from the gastrointestinal tract were more likely to be studied related to genes. It might be inferred that certain genes, such as HOTAIR and ASXL-1, appear in the table more than once, which shows that these molecules have carcinogenic abilities in any tissue. Conclusion: The epigenetic field is responsible for every advance on medical pathways to treat and discover cancer. This knowledge of cancer origin might lead to the creation of most effective drugs and the genes showed on this review may be specific targets for medicines in the future.

Occurrence of heavy metals in edible plants cannot be underestimated as these foodstuffs are important components of human diet. Intake of heavy metal-contaminated edible plants may pose a risk to the human health. The presence of heavy metals such as As, Cd, Pb, Zn, Co, Fe and Se was determined by using an atomic absorption spectrophotometry (AAS) method in the samples of the following edible plants obtained from the Bosnian markets: 1—Cichorium intybus L. var. foliosum Hegi, 2–Allium schoenoprasum L., 3–Allium porrum, 4—Plantago major, 5—Cucurbita maxima, 6—Asparagus officinalis, 7—Brassica oleracea var. Sabauda, 8—Beta vulgaris, 9—Brassica oleracea var. Acephala, 10—Solanum lycopersicum var. Cerasiforme, 11—Cynara scolymus, 12—Brassica rapa subsp. Rapa, 13—Plantago lanceolata, 14—Raphanus sativus, 15—Eruca sativa, 16—Valerianella locusta, 17—Beta vulgaris subsp. Vulgaris, 18—Atriplex hortensis, 19—Anthyllis vulneraria, 20—Brassica oleracea Gongylodes, 21—Brassica oleracea var. Italica, 22—Capsicum frutescens, 23—Physalis peruviana, 24—Phoenix dactylifera, 25—Aronia melanocarpa, 26—Prunus cerasus, 27—Rubus fruticosus, 28—Rubus idaeus, 29—Prunus domestica, 30—Vitis vinifera cvs. Cardinal, 31—Ficus, 32—Vaccinium myrtillus, 33—Vitis vinifera, 34—Mespilus germanica, 35—Vaccinium vitis-idaea, 36—Prunus domestica, 37—Juniperus communis, 38—Ocimum basilicum, 39–Rosmarinus officinalis, 40—Achillea millefolium, 41—Salvia officinalis, 42—Ocimum basilicum Purpurascens, 43—Foeniculum vulgare, 44—Hypericum perforatum and 45—Valerianella locusta. Essential elements, Zn, Fe, Co and Se were detected in the examined plant samples, while toxic heavy metals Pb and Cd were detected in some plants. Average consumption of these plants can provide the recommended daily intake of the essential nutrients and the consumption of such plants will not expose the consumer to the effects of toxic elements. However, there is a constant need to have routine monitoring of occurrence of potentially toxic elements in edible plant material in order to prevent possible heavy metal poisoning in long-term consumption of plants which contain such elements even only in traces.

Polymorphism exists in β-lactoglobulin (LGB) milk encoding gene in dairy animals, resulting in presence of different protein isoforms in milk. There is a link between genetic polymorphism in dairy proteins with technological properties of milk, milk yield and allergic reactions in humans. This study was conducted to identify LBG protein isoforms and their frequencies in population of Dubska Pramenka sheep breed. A total of 90 blood samples were genotyped using PCR-RFLP analysis. Genotypes were determined by PCR amplification followed by digestion with RsaI for identification of A and B alleles and using MspI for C allele identification. Two genetic variants (A and B) and three genotypes (AA, AB and BB) were identified. The presence of allele C in this study was not noticed. Gene frequencies of LGB A were 13; LGB B were 61; LGB AB were 61. There is no data on the genetic influence on the quality and quantity of milk from Dubska pramenka sheep, and there is need for further studies.

Prostate cancer is the most prominent cancer in men and one of the leading morbidity causes when referred to cancer. Prostate cancer usually affects men older than 65 but young men can also acquire cancer in specific conditions. Over the years, vast amounts of data about Prostate-Specific Antigen (PSA) levels were collected and together with novel mitochondrial DNA (mtDNA) copy number data can be used for risk assessment and prostate cancer diagnosis. This paper presents development of an Artificial Neural network (ANN) for classification between normal and prostate cancer patients based upon Prostate- Specific Antigen (PSA) levels and Mitochondrial DNA (mtDNA) copy number. For the development of Neural Network, samples of PSA level and mtDNA copy number were used. State of prostate was classified based on 352 samples as normal or cancerous with 175 samples being normal according to biopsy results and 177 being cancerous according to biopsy results. Among all tested architectures, the two-layer feedforward ANN with Logsig transfer function showed the best performance. An addition of k-fold cross validation method yielded better results with sensitivity was 100%, specificity 98.8% and overall accuracy of the system in subsequent validation was 99.4%.

The aim of this work is to study the alterations occurred in human cardiovascular system under artificially simulated microgravity. Artificial gravity produced by short-arm centrifuge along the head-to-feet axis induces gravity gradients and causes hemodynamic alterations. We have used differential arterial blood pressure measurements, pulse wave contour analysis, and accelerated photoplethysmography (APPG) to determine the impact of artificially simulated microgravity on human vascular system. The group of 50 healthy male volunteers was studied in a short-arm human centrifuge at normal gravity gradient of 1 Gz during 10 min at supine position lying at the nacelle. Blood pressure and APPG parameters registered before, during and after exposure of artificial gravity.

Logistic regression is widely used to model the relationship between a response variable and multiple independent variables. In practice, the most important variables for each problem domain are generally well known. However, a wealth of ongoing studies has been exploring additional variables for improving the prediction performance using an enriched model. In this article, a new method for ranking binary independent variables is suggested based on the distance between two decision boundaries. The boundaries correspond to the cases when value of the variable is zero or one. It is shown that, using age and body mass index as the base variables for diabetes prediction, the distances mentioned above are effective for ranking additional variables, leading to better scores than several conventionally used approaches.

This paper presents an Expert System for prediction of Anesthesia machines performance and inspection requirements. It consists of Artificial Neural Network and Fuzzy classifier. The system takes 12 inputs as follows: three for measured values of volume, three for measured gas concentration, three for visual inspection of the device, average utilization time of the anesthesia machine, preventive maintenance intervals and number of additional parts. For development of the system 197 samples were used. All samples were acquired during real-time study in healthcare institutions in Bosnia and Herzegovina during the period of three years. Two-layer feedforward back propagation network with 23 neurons in hidden layer and hyperbolic tangent sigmoid transfer function was trained with 158 samples. Out of 39 validation samples, the developed network was accurate in 97.44% cases. Fuzzy rules are defined according to recommendations. Validation of developed expert system was performed using 39 samples out of which expected results were obtained for 38 samples while for 1 sample false prediction of performance status of anesthesia machine was recorded.

Introduction: Managing working and personal life can result in conflicting demands for young medical students. An increasing number of students report concerns about the amount of stress in their life. This study was conducted to examine smoking and caffeine consumption and their relationship with stress as stress coping mechanisms among medical students. We aimed to estimate the prevalence of stress and its association with cigarette and caffeine substances induced behaviors. Substances found in cigarettes and caffeinated drinks (nicotine, caffeine, etc.) can trigger different neurological and endocrinological pathways which result in release or inhibition of other neuroactive substances, such as dopamine or adenosine, or hormones like cortisol. Methods: The data was collected from the original questioner created by the authors of this paper, which consisted of questions exploring stress symptoms, food, drink and tobacco related behavior patterns. Results: The statistical analysis of the collected data shows slightly different smoking patterns in male and female participants, but significant disproportion in genders when it comes to caffeinated drinks. The study concludes that there is a significant stress impact on caffeine and cigarette consumption, and thus affecting general health of the average medical student. Conclusion: It is necessary to provide and familiarize students with different stress-coping programs, which will in term have no, or less, side effects on their health and make the academic environment more suitable for coping with stress.

This paper presents an overview of biosensors used for industrial process control. The review was performed on twenty selected papers. Two widely used biosensors were analyzed: the biosensor for glycerol detection and the biosensor for detection of antibiotic residue in milk. In the case of glycerol detection, using whole bacterial cells of Gluconobacteroxydans showed highest sensitivity. In addition, an amperometric biosensor with gold electrode based on enzyme glycerol dehydrogenase with added diaphorase immobilized in polycarbamoyl sulfonate hydrogel showed appreciable results. For antibiotic detection, the parallel affinity sensor array, based on antibody binding, showed the best performance characteristics, with the detection limit of 0.12 μg/L for certain antibiotics.

Diabetes mellitus is a chronic disease that occurs due to a deficit in the secretion of insulin, or due to inadequate insulin action. Taking into consideration that diabetes mellitus is a chronic disease, thus it is unavoidable that a large number of diabetics, aside from their diabetes medicine, will be using other medication, which can cause interactions between the two types of drugs when they are combined. The aim of this project is to create a computer program which will aid a pharmacist during the process of dispensing diabetes medication, enabling him to check possible drug interactions and the safety of using certain types of drugs when drug pharmacodynamics and pharmacokinetics may be altered. Using C# and the MVC pattern, a program was developed which allows the examination of interactions between different drugs. By choosing the drugs of interest, the designed computer program is able to recognize if the given drug combination is safe, dangerous, or if it requires caution during administration. The program is also able to evaluate if the given diabetes medication is safe to use in special populations where drug pharmacodynamics and pharmacokinetics are altered. The application provides information that is easily and instantly available which can have a significant impact whilst working in pharmacy where the pharmacist needs to quickly make a decision regarding the safety of administration of a certain drug.

Drug dosage is the amount of a drug or medicinal substance, which needs to be administered to a patient in the form of a single dose or in the form of multiple doses, in order to achieve desirable therapeutic effect. Determining the adequate dose for a child represents a challenge, since the drug pharmacokinetics are different in the bodies of children, compared to those in adults, therefore children usually require lower doses of medication compared to adults. There are numerous formulas to calculate the appropriate drug dose for children, based on the child’s age, weight, etc. The aim of this project is to design a computer program that will calculate the drug dosage for children quicker, and requiring less effort. Using the programming language C#, a user interface was developed. The application enables calculating the dose for children based on the adult dosage and the age or weight of a child requiring the medication, and it also regards children under the age of one as a special group and enables the calculation of the dose for those children specifically. The application simplifies the work of a pharmacist in a drugstore in terms of dispensing medication for children and it can be also used by paediatricians while prescribing drugs for children.

Chromatic pupillometry represents a pioneering approach to the evaluation of inherited ocular diseases in childhood and a pilot study has been designed to evaluate its clinical utility. The physicians involved in the project belong to two different University centres: the data they gather must be collected in an electronic medical record reachable via web. Therefore, a specified medical record has been designed. It has been realized as a .NET application with RESTful architecture. The user-interfaces have been built with the aim to reduce the risk of error and with particular attention to usability, according to standards. Each web page of the medical record has been made as user-friendly as possible. Thanks to these characteristics, the physicians have a good attitude toward the use of the electronic medical record as a way to improve the progression of the pilot study.

Global mobility including all countries in the world, is growing at a rate faster than the world’s population, which is surpassed 244 million people in 2015. The explosive growth in the importance, interest and the study of international migration urges new developments for accessible, efficient and affordable global public health systems. In order to actualize such improvements and eliminate the undesirable consequences of wrong or late diagnosis in global public healthcare, we propose an intelligent healthcare diagnostics engine. Current diagnosis systems have obstacles about easy user access by worldwide heath seekers. In this study, it is aimed to reach patients using different languages while providing an opportunity to enter symptoms in their everyday language text, besides medical expressions of symptoms. Language independency is provided on the background of user interface by using translate functions in TextBlob, python. Named entity recognition (NER) techniques, based on natural language processing (NLP), are applied to develop language independent predictive model. Extracted terms are implied as an input of the model and analyzed for degree of matching symptoms for the corresponding diagnosis. The accuracy at a range of 20 and 100% has been accomplished based on the degree of matching of patient’s enquiry with database of the system, for languages other than English.

In this research, we aimed to combine three areas of science; pharmacy and bioengineering, as well as the small part of information technology, in an effort to solve the evergrowing problem of personalized drugs, in this case, suppositories. Various studies have shown that the person’s preferences and adherence to medicine are influenced by the characteristics of the product, in the case of suppositories, mainly by shape. We have obtained all of the existing information regarding vaginal and rectal abnormalities, which we have incorporated into computer software, making it possible to suggest the most adequate and appropriate shape of suppositories for each patient. Considering the high price of personalized drugs and the emergence of new trends in bioengineering, we have come to the idea of including three-dimensional printing, which has recently had a breakthrough in these areas of science and also proved to be a very powerful new tool for future development in pharmaceutics. We have managed to make different moulds for rectal and vaginal suppositories, despite the fact that there are no studies on the topic of three-dimensional printing of moulds for suppositories. We also created a software tool for predicting the optimal shape of the suppositorie.

Microneedles facilitate transdermal drug delivery by piercing microscale pores through the stratum corneum. They usually penetrate only thought the stratum corneum thus the nociceptors of the skin will not be stimulated. Therefore, as an alternative approach, microneedles provide a minimally invasive method for drug delivery. Additive manufacturing which is called threedimensional (3D) printing revolutionized the field of pharmaceutical and biomedical sciences due to their capabilities for fast and cost-effective prototyping of complex structures. Biodegradable 3D printed PLA microneedles are an emerging class of novel transdermal drug delivery systems. Aims of this study were to fabricate 3D printed microneedles and investigate for the first time the ability to coat different drug formulations on 3D printed microneedles. We demonstrated that 3D printing combined with the post-fabrication etching step could make ideally sized and shaped microneedles. Dip coating method revealed to be the best coating method for 3D printed microneedles because of its simplicity and ability to create a uniform load over the printed microneedles. We have also shown that 3D printed microneedles could successfully penetrate and break off into porcine skin.

Amenorrhea is defined as the absence of menstrual bleeding and it is classified as primary, as the absence of menarche and secondary, usually longer than six to twelve months. The causes of secondary amenorrhea are pathological changes of female reproductive organs and hypothalamic-pituitary axis which, due to complex pathophysiology, are difficult to differentiate. Amenorrhea is associated with other disorders such as anxiety and depression, osteoporosis, cardiovascular diseases, endometrial cancer and infertility. Therefore, the importance of accurate diagnosis and consequent treatment is indisputable. For the purpose of accurate diagnosis, there has been developed an application based on the selected algorithm used for the evaluation of secondary amenorrhea. Algorithm allows healthcare workers and patients to make a decision on health protection based on the best evidence and to minimize costs and time frame of testing, as well. During the preparation of AmnSec application, there were used reference intervals on the following biochemical parameters: prolactin, TSH, FSH, testosterone, DHEAS and presence of virilization. The combination of default values offers the possible cause of secondary amenorrhea while the diagnostic success of the application entirely depends on the accuracy of the algorithm that the application is based on. The development of this type of application makes it easier for patients to access valid information by simply using their personal computers or mobile phones. Further work and the progress of the information sector in medicine is needed to provide more efficient, faster and better care and higher quality information for patients as the axis of improving health and life quality.

Oral delivery is one of the most common ways of drug administration because of its simplicity. However, this method of delivery can be limited for many drugs like peptides or proteins. Scientists have been trying to enable oral delivery of this kind of structures for decades. Because intestine does not have sharp pain receptors like skin, the insertion of microneedles would not be painfully. Modelled by previous research, we tried to formulate sugar microneedles that contain active substance (ascorbic acid) and incorporate them into the acid-resistant capsules. We have chosen sugar because of its ability to dissolve into the intestine. 3D printed microneedles were used as a model for the preparation of different silicon molds. These molds were used for sugar microneedles. Different types of sugar showed different types of performance, for example, a combination of two sugars resulted to be the best in our case. Our next step after successfully produced sugar microneedles is focused on their ability to dissolve into the intestine. Using acidic and basic medium we have examined the behavior of the sugar microneedles formulation that we put into acid-resistant capsules.

Biofilms are microorganisms that play a huge role in various fields of study. Bacterial ability for biofilm formation can be examined in the presence of different host substances which may affect the biofilm formation capability in different ways. Synthetically used hormones are substances used by patients in order to supply their hormonal deficit. One of the most widely used synthetically-produced hormones is insulin. The hormone is used for treatment of diabetes patients. In our study we examined the antibacterial effect of several V/V solutions of commercially available insulin as well as the biofilm forming capacity for the following bacterial strains: Staphylococcus aureus ATCC 25923, Escherichia coli ATCC 25922, a clinical strain of Escherichia coli and a clinical strain of methicillin-resistant Staphylococcus aureus (MRSA). The results of our study showed that insulin detemir does not have any antibacterial capabilities for the four tested bacterial strains. The results also indicate that Staphylococcus aureus ATCC 25923 mixed with a V/V insulin detemir diluted suspension at all tested concentrations (from 10% to 10−8%) elevated biofilm formation while the other three tested strains showed no change in biofilm formation upon addition of insulin. This refers to a utilization process of the insulin detemir suspension from the three mentioned bacterial strains. From this it is evident that the effect different drugs have on the biofilm forming capacity of bacteria is significant in ordinating therapy for patients who take the drug of choice on a regular basis.

Over the past ten years, technology has been developed to the point, where it can enable continuous and efficient monitoring of blood glucose levels for patients with diabetes mellitus. The biggest step forward was demonstrated by biosensors, which, with a non-invasive approach, provide healthcare workers with the information required for good titration of insulin doses. We looked at the benefits of using biosensors in diabetes monitoring in terms of medical aspect and economic justification of replacing traditional test strips with biosensors. In this paper, we have shown potential benefits in terms of improving diabetes control, patient benefits, and how the medical benefit is collerating with the economic viability of biosensors use. On the territory of Bosnia and Herzegovina test strips for glucose control are still in use. This paper includes an analysis of the costs of traditional monitoring and monitoring using biosensors. We also reviewed the monitoring of diabetes in neighboring countries such as Croatia, Slovenia, Montenegro, and Serbia in order to compare them with the current situation in Bosnia and Herzegovina.

Attention Deficit Hyperactivity Disorder (ADHD) is characterized by difficulties in modulating attention and hyperactivity/impulsivity. It is a very common disorder in childhood compromising school performance, hampering interpersonal relationships and causing low self-esteem that can continue in adult life and bring even more damage to the execution of routine activities in patients lives. The most commonly used treatment for ADHD is through psychostimulant drugs, however, association with other therapies is important to ameliorate the symptoms of hyperactivity. There by the treatment should be multidisciplinary, where several professionals with the family should be accompanying and treating individuals with ADHD. The objective of this study was to highlight the importance of early diagnosis and the contribution of knowledge acquisition on the nuances in the diagnosis of ADHD in adults even during medical training and multidisciplinary therapeutic procedures to improve the symptoms of adult patients with ADHD. It is concluded that the pharmacological treatment is quite effective, mainly regarding the use of methylphenidate as psychostimulant, presenting a very satisfactory profile of side effects. In some individuals with the disorder, pharmacological treatment is not sufficient because the symptoms persist or there are comorbidities. In these cases, multidisciplinary treatment with psychopharmaceuticals, psychotherapies, school and family follow-up is necessary to alleviate symptoms, leading individuals with ADHD to participate in activities common to all in the family and in society, thus preventing conduct disorders and delinquency. Therefore, the early diagnosis of ADHD with a correct treatment institution is essential for a better prognosis of the patient.

Mammography is a medical imaging technique which utilizes low-energy X-rays specifically for imaging of breast tissue. Being able to classify mammographic tumors as benign or malignant in the early diagnostic stages can help decrease the amount of subsequent examinations, thus decreasing the associated inappropriate diagnostics (such as false-positives and false-negatives). The following paper describes a method using an artificial neural network in order to predict the severity of a mammographic tumor as either benign or malignant, in order to enhance the overall digital diagnostic procedure of mammographic screening. A feedforward neural network architecture was developed using a data set provided by Institute of Radiology at University Erlangen-Nuremberg. K-fold cross validation was utilized in artificial neural network training, and the effect of varying quantities of neurons in the hidden layer was evaluated by assessing the system output. The single-layer, feedforward neural network architecture created, with 80 neurons in hidden layer, achieved the best performance. The overall structure resulted a sensitivity of 85.0%, specificity of 81.0%, and accuracy of 82.9% in classifying mammographic tumors as benign or malignant.