We investigated DAB1-protein deficiency in the inner-ear development of yotari in comparison to humans and wild-type (wt) mice by immunofluorescence for the expression of connexins (Cxs) and the pannexin Panx1. The spatial and temporal dynamics of Cx26, Cx32, Cx37, Cx40, Cx43, Cx45, and Panx1 were determined in the sixth and eighth weeks of human development and at the corresponding mouse embryonic E13.5 and E15.5, in order to examine gap junction intercellular communication (GJIC) and hemichannel formation. The quantification of the area percentage covered by positive signal was performed for the epithelium and mesenchyme of the cochlear and semicircular ducts and is expressed as the mean ± SD. The data were analysed by one-way ANOVA. Almost all of the examined Cxs were significantly decreased in the cochlear and semicircular ducts of yotari compared to wt and humans, except for Cx32, which was significantly higher in yotari. Cx40 dominated in human inner-ear development, while yotari and wt had decreased expression. The Panx1 expression in yotari was significantly lower than that in the wt and human inner ear, except at E13.5 in the mesenchyme of the wt and epithelium and mesenchyme of humans. Our results emphasize the relevance of GJIC during the development of vestibular and cochlear functions, where they can serve as potential therapeutic targets in inner-ear impairments.

Background: We could say that traditional healing is a way of healing that has been common since ancient times. It has been passed down from generation to generation for many centuries. Magic medicine, although not approved by any of the monotheistic religions present in Bosnia and Herzegovina, and strictly prohibited by Islam, in the form of various magical acts and spells, exists among the people. Some of these magical practices have their roots in the pre-Christian Slavic period and earlier. Objective: The aim of this article was to provide the review of the traditional medicine during the history and today in Bosnia and Herzegovina. Methods: Review of the available literature, personal contacts and personal experience in contact with the traditional medcine. Discussion: Some of these magical practices have their roots in the pre-Christian Slavic period and earlier. Since the cause of the disease was usually associated with evil beings of supernatural powers, a deity or God’s will or punishment, it is understandable that priests have long been engaged in healing. Especially in the mentally ill, there seemed to be a certain divine or demonic origin of the disease. Muslim folk medicine divides diseases into two groups; in fevers and obsessions with unclean spirits. Folk medicine knows the healing properties of herbs and other substances of animal or mineral origin. The medicinal properties of simple foods that can be found in every home are also widely used, such as: milk, honey, vinegar, oil, onion, and garlic. Prescription books, known as “ljekaruše”, were created by collecting and writing down folk remedies. They were written mostly by Catholic priests. “Witch doctors” or “healers” have been preserved in Orthodox monasteries. Conclusion: Traditional medicine is important for history of medicine, ethnology, anthropology, and abounds in folklore elements. It is an area that leads to knowing, understanding or feeling the very nucleus of a nation.

Acta Informatica Medica journal (www.actainformmed.org), as Biomedical Informatics journal, during past 30 years of existing played important role in distribution of knowledge and experience within this scientific field, by publishing contributions of the biomedical experts from worlwide and spreading of Biomedical informatics knowledge and experiences in scientific and academic community. Acta Informatica Medica journal has been founded in the year 1993 by Izet Masic and Zoran Ridjanovic, as official journal of Bosnian-Herzegovinan Society of Medical Informatics (BHSMI). In the year 2019 Acta Informatica Medica has been accepted as official journal of the European Federation for Medical Informatics (www.efmi.org), besides 3 other journals: International Journal of Medical Informatics, Methods of Information in Medicine and European Journal of Biomedical Informatics. Journal Acta Informatica Medica is abstracted and indexed in 30 on-line data bases, including Pubmed, Pubmed Central, Scopus, Embase, Hinari, etc. The journal follows the Guidelines and recommendations of ICJME, COPE, EASE, WAME, etc. as well as the recommendations of the “Sarajevo Declaration on Integrity and Visibility of Scholarly Journals”, accepted by 17 Editors of biomedical journals at “SWEP 2018” Conference held in Sarajevo and printed in the countries in South-Eastern Europe. The journal supports presentations at conferences held in Bosnia and Herzegovina. The abstract papers presented at “The Mediterranean Seminar on Science Writing, Editing and Publishing“ – “SWEP 2016”, “SWEP 2018”; “SWEP 2020” and “SWEP 2021”, also found its place in the journal, by which we met our goal of promoting science and scientific publication at the area of Bosnia and Herzegovina and other countries in the region. Acta Informatica Medica has been ranked: Highest Impact Factor for 2011–2022 was 1.496 and Lowest Impact Factor for 2011–2022 was 0.59. During the year 2021 in Acta Informatica Medica journal was published 46 papers. From total amount published papers, 67,39% was original papers, where it was more published original papers in the journal than in the year 2020. Acta Informatica Medica has value of important metrics (last updated on November 16, 2021): Impact Score - 1.50, h-Index - 20, Rank - 15980, SJR - 0.267.

Background: Arrhythmias are common problems in hypertensive patients. The presence and complexity of both supraventricular and ventricular arrhythmias may influence morbidity, mortality, as well as the quality of life of patients. Objective: The aim of this study was to assess the diagnostic value of combined 24h BP and ECG Holter monitoring in detection of cardiac arrhythmias in patients with arterial hypertension. Methods: We analyzed the simultaneous records of combined 24h BP and ECG Holter monitoring for 356 adult patients with diagnosed arterial hypertension in the period from January 2017 until January 2021 year. The cardiac arrhythmias were classified in three main groups as following: a) Supraventricular arrhythmias; b) Ventricular arrhythmias; c) Bradyarrhythmia’s. Standard transthoracic echocardiograms were performed in order to evaluate signs of hypertensive or structural heart disease with focus on left ventricle hypertrophy and LV function. Results: Patients had a mean age of 64 ± 11years, 62% male. Average clinic BP was 153.4+18/87.5+14 mmHg. More than 46% of patients displayed a very high-risk profile. In all enrolled patients, cardiac arrhythmia was detected in 302 (84%) patients. The total number of patients with supraventricular arrhythmias was 153 (50,7%). Ventricular arrhythmias were detected in 98 (32,5%) patients. Bradyarrhythmia’s were detected in 51 (16,9%) patients. Elevated resting heart rate in sinus rhythm was detected in 87 (31,6%) of 275 patients with sinus rhythm. Conclusion: Most arrhythmias are related to longstanding arterial hypertension. Effective treatment of arterial hypertension plays important role in preventing structural and functional cardiac abnormalities which will contribute to the reduction of cardiac arrhythmias in hypertensive patients.

BACKGROUND The pre-analytical phase, which includes all preparatory actions to the analytical procedure, is part of the process during which there is the greatest possibility of laboratory errors. This study was conducted to investigate the frequency and types of laboratory errors during work in the clinical laboratory as well as the frequency and types of laboratory errors in the pre-analytical phase of laboratory work. METHODS The retrospective, descriptive study covered the period from 01/01/2016 to 12/31/2016 within which the presence of 5 different indicators of quality of work, i.e., pre-analytical errors, was monitored: improperly drawn blood, coagulated blood sample, hemolyzed blood sample, improperly marked referral for analysis, and insufficient sample for analysis. RESULTS The most common error in the pre-analytical phase of our study was "coagulated sample", followed by: "improperly drawn blood", "improperly marked referral", "insufficient sample for analysis", and "hemolyzed sample". Using the chi-squared test, a statistically significant difference was found in the frequency of occurrence of certain types of indicators in different departments (p < 0.005). CONCLUSIONS Reduction of these errors can be achieved through analyzing and correcting the reasons for them, education, and by joint action of experts and international organizations, continual training of staff as well as to following the adopted guidelines and standards.

Background: After the World Health Organization declared the outbreak of a new coronavirus on 30 January 2020 a public health emergency of international importance, health authorities in Bosnia and Herzegovinaas in other countries around the world, have ordered active surveillance, early detection, isolation and management, cases, contact monitoring and prevention of the spread of infection. Objective: The aim of this study was to describe and analyze of the organization of family medicine during COVID-19 pandemic in Canton Sarajevo with its positive and negative aspects. Methods: The case study design provided an ideal framework for systematic research into the organization of primary health care in Sarajevo Canton during the COVID-19 pandemic as it is an empirical study exploring a contemporary phenomenon within its real-life context when the boundaries between phenomenon and context are not clearly visible. Multiple sources of evidence are used. Data were collected in several different ways: analyzing policies, laws, regulations, decisions related to the COVID pandemic, insight into changes in the health information system, collecting data from reports, and through a group interview (Delphi exploratory) with eleven family medicine specialists. Results: Primary care was organized as two parallel systems with family medicine in the center. The first system was COVID-19 primary care and the second was regular care for non-COVID-19 patients. Family medicine physicians despite a numerus setbacks provide health care for 106346 COVID-19 cases. Discussion: Every principal (first contact access, person-centered care, comprehensiveness, continuity of care, community based, coordination of care, and holistic modeling) of family medicine was interrupted with consequences for patients and family physicians. Conclusion: Additional research is needed to examine all facets of the family medicine and primary health care response to the COVID-19 pandemic in Sarajevo Canton.

This study was intended to determine the effect of adding flax seeds to a concentrate for lamb fattening on the fatty acid composition of the omental fat depot in Pramenka lambs reared indoors. A total of 63 lambs (10±3 kg of live body weight, 30±7 days of age, 30 males and 33 females) were used. They were divided into two groups: a control (CON) fed on hay, ewe's milk, and a 300-g daily ration of a commercial concentrate, and an experimental group (FS) fed on hay, ewe's milk and 300 g/day of the concentrate enriched with 5% of flax seeds. After a 60-day fattening period for each group, 10 lambs (5 males and 5 females) were selected and omental fat samples were analysed for fatty acid composition. Highly significant differences (p⟨0.001) were found between CON and FS in α-linolenic acid, the sum of n-3 fatty acids, and the ratio n-6/n-3 fatty acids. The effect of sex on the fatty acid content in the fat depot was only significant for C20:0 fatty acid (p⟨0.05).

Automatic modulation classification (AMC) is a promising technology for identifying modulation types, and deep learning (DL)-based AMC is one of its main research directions. Conventional DL-based AMC methods are centralized solutions (i.e., CentAMC), which are trained on abundant data collected from local clients and stored in the server and generally have advanced performance, but their major problem is the risk of data leakage. Besides, if DL-based AMC is only trained with the data from their corresponding clients, it may exhibit weak performance. Thus, a federated learning (FL)-based AMC (FedeAMC) is proposed under the condition of class imbalance and noise varying. Its advantage is low risk of data leakage without severe performance loss, because data and training are in each local client, while only knowledge (i.e., gradient or model weight), rather than data, is shared with the server. In addition, there is generally class imbalance problem in each local client, and balanced cross entropy is introduced as loss function for solving this problem. Simulation results demonstrated that average accuracy gap between FedeAMC and CentAMC is less than 2%.

Radio frequency fingerprint (RFF) identification is a popular topic in the field of physical layer security. However, machine learning based RFF identification methods require complicated feature extraction manually while deep learning based methods are hard to achieve robust identification performance. To solve these problems, we propose a novel RFF identification method based on heat constellation trace figure (HCTF) and slice integration cooperation (SIC). HCTF is utilized to avoid the manual feature extraction and SIC is adopted to extract more features automatically in RF signals. Experimental results show that our proposed HCTF-SIC identification method can achieve higher accuracy than the existing RFF methods. The identification accuracy achieves 91.07% when SNR <inline-formula> <tex-math notation="LaTeX">$\pmb {=}$ </tex-math></inline-formula> 0 dB and it is even higher than 99.64% when the SNR <inline-formula> <tex-math notation="LaTeX">$\pmb {\ge }$ </tex-math></inline-formula> 5 dB.

Due to the implementation and performance limitations of centralized learning automatic modulation classification (CentAMC) method, this paper proposes a decentralized learning AMC (DecentAMC) method using model consolidation and lightweight design. Specifically, the model consolidation is realized by a central device (CD) for edge device (ED) model averaging (MA) and multiple EDs for ED model training. The lightweight is designed by separable convolutional neural network (S-CNN), in which the separable convolutional layer is utilized to replace the standard convolution layer and most of fully connected layers are cut off. Simulation results show that the proposed method substantially reduces the storage and computational capacity requirements of the EDs and communication overhead. The training efficiency also shows remarkable improvement. Compared with convolutional neural network (CNN), the space complexity (i.e., model parameters and output feature map) is decreased by about 94% and the time complexity (i.e., floating point operations) of S-CNN is decreased by about 96% while degrading the average correct classification probability by less than 1%. Compared with S-CNN-based CentAMC, without considering model weights uploading and downloading, the training efficiency of our proposed method is about <inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> times of it, where <inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> is the number of EDs. Considering the model weights uploading and downloading, the training efficiency of our proposed method can still be maintained at a high level (e.g., when the number of EDs is 12, the training efficency of the proposed AMC method is about 4 times that of S-CNN-based CentAMC in dataset <inline-formula> <tex-math notation="LaTeX">$D_{1} = \{2{\mathrm {FSK, 4FSK, 8FSK, BPSK, QPSK, 8PSK, 16QAM}}\}$ </tex-math></inline-formula> and about 5 times that of S-CNN-based CentAMC in dataset <inline-formula> <tex-math notation="LaTeX">$D_{2} = \{2 {\mathrm {FSK, 4FSK, 8FSK, BPSK, QPSK, 8PSK, PAM2, PAM4, PAM8, 16QAM}}\}$ </tex-math></inline-formula>), while the communication overhead is reduced more than 35%.

Background Most trials comparing endovascular treatment (EVT) alone versus intravenous thrombolysis with alteplase (IVT) + EVT in directly admitted patients with a stroke are non-inferiority trials. However, the margin based on the level of uncertainty regarding non-inferiority of the experimental treatment that clinicians are willing to accept to incorporate EVT alone into clinical practice remains unknown. Objective To characterize what experienced stroke clinicians would consider an acceptable level of uncertainty for hypothetical decisions on whether to administer IVT or not before EVT in patients admitted directly to EVT-capable centers. Methods A web-based, structured survey was distributed to a cross-section of 600 academic neurologists/neurointerventionalists. For this purpose, a response framework for a hypothetical trial comparing IVT+EVT (standard of care) with EVT alone (experimental arm) was designed. In this trial, a similar proportion of patients in each arm achieved functional independence at 90 days. Invited physicians were asked at what level of certainty they would feel comfortable skipping IVT in clinical practice, considering these hypothetical trial results. Results There were 180 respondents (response rate: 30%) and 165 with complete answers. The median chosen acceptable uncertainty suggesting reasonable comparability between both treatments was an absolute difference in the rate of day 90 functional independence of 3% (mode 5%, IQR 1–5%), with higher chosen margins observed in interventionalists (aOR 2.20, 95% CI 1.06 to 4.67). Conclusion Physicians would generally feel comfortable skipping IVT before EVT at different certainty thresholds. Most physicians would treat with EVT alone if randomized trial data suggested that the number of patients achieving functional independence at 90 days was similar between the two groups, and one could be sufficiently sure that no more than 3 out of 100 patients would not achieve functional independence at 90 days due to skipping IVT.

Architectural patterns are solutions to common problems in software design. These usually tackle one or more customer requirements (business, functional, or quality requirements). As continuous deployment becomes more important for satisfying customer’s experience in software projects, there is a greater need in supporting continuous integration as its prerequisite. The nature of architectural design patterns is that some are more suitable for continuous integration then others. However, the existing approaches do not prescribe how to tailor architectural design considering integration challenges.To identify patterns suitable for continuous integration, we present a methodology for identification of architectural design patterns that support continuous integration based on continuous assessment. Our methodology, based on Aglie, enables DevOps engineers to assess their integration experience considering design changes, implementation changes, and creation of new version deliverables. The methodology complements common DevOps activities and introduces templates for communicating feedback from DevOps engineers to architects. Architects handle the communicated feedback as requirements and optimise their design accordingly. In this way, the design decisions take shape of solution patterns that, besides other existing requirements, satisfy requirements necessary to facilitate continuous integration.

Background: COVID-19 infection has shown many complications on all organ systems, including the pancreas, during the acute phase of infection and in the post covid period. Objective: Our goal was to compare the frequency of patients with type 1 and type 2 diabetes in the Outpatient Clinic “Srce Sarajeva”, in the year before COVID-19, 2019, and during the COVID-19 infection, in 2020 and 2021. Our second goal was to monitor the incidence of diabetes after COVID-19 infection, the time of onset after the acute phase of the disease, and treatment options for individual patients depending on the value of glucose. Methods: The study was designed as a retrospective-prospective, with the consent of the Director of the Outpatient Clinic “Srce Sarajeva”, and patient consent, in the period of January 2019 to December 2021. The study included 371 patients at the age between 18-70. Results: In 2020 and 2021 there was a significant difference in the number of patient diagnosed with diabetes who came for examination, compared to 2019. The number of new-onset diagnosed patients with type 1 and type 2 diabetes was significantly higher in 2020 and 2021 compared to 2019. In 2020, out of five newly discovered type 1, 3 of them, with an average age of 23 (+/- 1-4), overcame COVID-19 infection, and diabetes was detected 3-4 weeks after overcoming COVID-19 infection. Of the 122 type 2 patients, 19 were newly diagnosed, 47 were of average age (+/- 2-6), 13 were COVID-19 infected, and diabetes was detected 4-6 weeks after infection. In 2021, out of 4 newly discovered type 1, 3 of them, with an average age of 22 (+/- 1-2), overcame COVID-19 infection, and diabetes was detected 2-3 weeks after overcoming COVID-19 infection. Of the 114 type 2 patients, 32 were newly diagnosed, 45 were of average age (+/- 2-6), 23 were COVID-19 infected, and diabetes was detected 6-8 weeks after infection. Conclusion: COVID-19 infection adversely affects the pancreatic tissue leading to the clinical picture of type 1 and type 2 diabetes, and all patients, especially those at high risk of developing the disease suggest blood sugar testing, 3-4 weeks after the acute phase of the disease, and earlier if they were on corticosteroid therapy.