Aim To analyse prevalence of metabolic syndrome (MS) in kidney transplant recipients at the University Clinical Centre Tuzla in Bosnia and Herzegovina (B&H), and determine effects of a modern drug therapy in achieving target metabolic control in kidney transplant patients. Methods A single-centre prospective study that included 142 kidney transplant patients over one year follow-up period was conducted. Patient data were collected during post-transplant periodical controls every 3 months including data from medical records, clinical examinations and laboratory analyses. Results Out of 142 kidney transplant patients, MS was verified in 85 (59.86%); after a pharmacologic treatment MS frequency was decreased to 75 (52.81%). After a one-year period during which patients were receiving therapy for MS, a decrease in the number of patients with hyperlipoproteinemia, decrease in average body mass index (BMI), glycemia and haemoglobin A1C (HbA1C) were observed. Hypertension did not improve during this period, which can be explained by transplant risk factors in the form of immunosuppressive drugs and chronic graft dysfunction. Conclusion A significant reduction in components of the metabolic syndrome after only one year of treatment was recorded, which should be the standard care of kidney transplant patients.

Ixodid ticks are distributed across all countries of the Western Balkans, with a high diversity of species. Many of these species serve as vectors of pathogens of veterinary and medical importance. Given the scattered data from Western Balkan countries, we have conducted a comprehensive review of available literature, including some historical data, with the aim to compile information about all recorded tick species and associated zoonotic pathogens in this region. Based on the collected data, the tick fauna of the Western Balkans encompasses 32 tick species belonging to five genera: Ixodes , Haemaphysalis , Dermacentor , Rhipicephalus and Hyalomma . A range of pathogens responsible for human diseases has also been documented, including viruses, bacteria and parasites. In this review, we emphasize the necessity for integrated surveillance and reporting, urging authorities to foster research by providing financial support. Additionally, international and interdisciplinary collaborations should be encouraged that include the exchange of expertise, experiences and resources. The present collaborative effort can effectively address gaps in our knowledge of ticks and tick-borne diseases. Graphical Abstract

A 2-year study was done to compare fruit morphological and chemical composition of three nectarine cultivars grown in south Hercegovinia conditions. A high variability among and within cultivars was found and significant differences were observed among them in all properties analyzed. On the basis of evaluated data, the best fruit performance was registered in ‘Caldesi 2000’ and ‘Venus’ grown in the condition of this part of the Mediteran. This evaluation may help to select a set of nectarine cultivars with better fruit quality attributes, which in our growing conditions might be indicated in ‘Caldesi 2000’ and somewhat in ‘Venus’. The highest average of fruit width (61.18 mm) and fruit weight (148.24 g) was found in cultivar Caldesi 2000. As for friut thickness, also cultivar Caldesi 2000 had the highest value (55.39 mm). The results for the highest fruit length (60.48 mm) had Venus cultivar also fruit stone weight length, width and thickness. The contents sugars (glucose, fructose) total soluble dry matter, and total acids in fruits were found in cultivar Venus, but pH and sucrose were found in cultivar Sun Grand.

Darwinian evolution, including the selection of the fittest species under given environmental conditions, is a major milestone in the development of synthetic living systems. In this regard, generalist or specialist behavior (the ability to replicate in a broader or narrower, more specific food environment) are of importance. Here we demonstrate generalist and specialist behavior in dynamic combinatorial  libraries composed of a peptide-based and an oligo(ethylene glycol) based building block. Three different sets of macrocyclic replicators could be distinguished based on their supramolecular organization: two prepared from a single building block as well as one prepared from an equimolar mixture of them. Peptide-containing hexamer replicators were found to be generalists, i.e. they could replicate in a broad range of food niches, whereas the octamer peptide-based replicator and hexameric ethyleneoxide-based replicator were proven to be specialists, i.e. they only replicate in very specific food niches that correspond to their composition. However, sequence specificity cannot be demonstrated for either of the generalist replicators. The generalist versus specialist nature of these replicators was linked to their supramolecular organization. Assembly modes that accommodate structurally different building blocks lead to generalist replicators, while assembly modes that are more restrictive yield specialist replicators.

We report on the development of a novel pixel charge readout system, Grid Activated Multi-scale pixel readout (GAMPix), which is under development for use in the GammaTPC gamma ray instrument concept. GammaTPC is being developed to optimize the use of liquid argon time projection chamber technology for gamma ray astrophysics, for which a fine grained low power charge readout is essential. GAMPix uses a new architecture with coarse and fine scale instrumented electrodes to solve the twin problems of loss of measured charge after diffusion, and high readout power. Fundamentally, it enables low noise and ultra low power charge readout at the spatial scale limited by diffusion in a time projection chamber, and has other possibly applications, including future DUNE modules.

The Sustainable Development Goals (SDGs) of the United Nations provide a blueprint of a better future by "leaving no one behind", and, to achieve the SDGs by 2030, poor countries require immense volumes of development aid. In this paper, we develop a causal machine learning framework for predicting heterogeneous treatment effects of aid disbursements to inform effective aid allocation. Specifically, our framework comprises three components: (i) a balancing autoencoder that uses representation learning to embed high-dimensional country characteristics while addressing treatment selection bias; (ii) a counterfactual generator to compute counterfactual outcomes for varying aid volumes to address small sample-size settings; and (iii) an inference model that is used to predict heterogeneous treatment-response curves. We demonstrate the effectiveness of our framework using data with official development aid earmarked to end HIV/AIDS in 105 countries, amounting to more than USD 5.2 billion. For this, we first show that our framework successfully computes heterogeneous treatment-response curves using semi-synthetic data. Then, we demonstrate our framework using real-world HIV data. Our framework points to large opportunities for a more effective aid allocation, suggesting that the total number of new HIV infections could be reduced by up to 3.3% (~50,000 cases) compared to the current allocation practice.

Pored oblika i ukrasa, natpisi predstavljaju najkarakterističniji i najznačajniji faktor naučne i umjetničke vrijednosti stećaka. Kada je poznato vrijeme nastanka natpisa, onda istraživači imaju bolja polazišta za svestranije proučavanje stećaka. Prije svega, datacija natpisa značajno pomaže u praćenju razvoja jezika i pisma. Svaki datirani stećak predstavlja značajnu i stabilnu stepenicu na slabije poznatom putu u razvoju srednjovjekovnog pisma. Na ovom mjestu dajemo prilog dataciji natpisa na stećku Vukašina Dobrašinovića iz Vrsinja u naselju Konjsko u blizini Trebinja. Ranije ponude datiranja ukazuju na odstupanjameđu vrsnim epigrafičarima i prave dodatne nejasnoće na polju epigrafike. Novim arhivskim pokazateljima historijat Dobrašinovića iz Vrsinja dobija svoje konture. Egzaktno utvrđena životnost Vukašina Dobrašinovića (1421-1428) je relevantna polazna osnova za datiranje natpisa na njegovom nadgrobnom spomeniku pa time i jasnija osnova za daljnje proučavanje jezika i pisma. 

U antičko doba bile su prisutne predstave zmija u mnogim mitovima i kultovima. Zmija je često bila simbol života i smrti. Kao kultna životinja javlja se u Mitraizmu, a kao simbol zla javlja se u hrišćanskoj tradiciji. Na području velikog rudarskog nalazišta Japra pronađena su dva ulomka keramike sa predstavama zmija koje su bile omotane oko drške. Prema analogijom sa sličnim slučajevima može se reći da su ove posude povezane sa kultom Mitre i korišteni u vjerske svrhe.  

We assess proton decay signatures in the simplest viable $SU(5)$ model with regard to constraints on parameters governing the Standard Model fermion mass spectrum. Experimental signals for all eight two-body proton decay processes result from exchange of two gauge bosons, a single scalar leptoquark, or their combination. Consequently, it enables us to delve into an in-depth anatomy of proton decay modes and anticipate future signatures. Our findings dictate that observing a proton decay into $p\to\pi^0e^+$ indicates gauge boson mediation, with the potential for observation of $p\to\eta^0e^+$ mode. Alternatively, if decay is through $p\to K^+\overline\nu$ process, it is mediated by a scalar leptoquark, possibly allowing the observation of $p\to\pi^0\mu^+$. Detection of both $p\to\pi^0 e^+$ and $p\to K^+\overline\nu$ could enhance $p\to\pi^0\mu^+$ through constructive interference. The model predicts inaccessibility of $p\to\pi^+\overline\nu$, $p\to\eta^0\mu^+$, $p\to K^0e^+$, and $p\to K^0\mu^+$, regardless of the dominant mediation type, in the coming decades. In summary, through a comprehensive analysis of proton decay signals, gauge coupling unification, and fermion masses and mixing, we precisely constrain the parameter space of the $SU(5)$ model in question.

Frontal polymerization (FP) is a self-sustaining curing process that enables rapid and energy-efficient manufacturing of thermoset polymers and composites. Computational methods conventionally used to simulate the FP process are time-consuming, and repeating simulations are required for sensitivity analysis, uncertainty quantification, or optimization of the manufacturing process. In this work, we develop an adaptive surrogate deep-learning model for FP of dicyclopentadiene (DCPD), which predicts the evolution of temperature and degree of cure orders of magnitude faster than the finite-element method (FEM). The adaptive algorithm provides a strategy to select training samples efficiently and save computational costs by reducing the redundancy of FEM-based training samples. The adaptive algorithm calculates the residual error of the FP governing equations using automatic differentiation of the deep neural network. A probability density function expressed in terms of the residual error is used to select training samples from the Sobol sequence space. The temperature and degree of cure evolution of each training sample are obtained by a 2D FEM simulation. The adaptive method is more efficient and has a better prediction accuracy than the random sampling method. With the well-trained surrogate neural network, the FP characteristics (front speed, shape, and temperature) can be extracted quickly from the predicted temperature and degree-of-cure fields.

Introduction: Covert brain infarcts (CBI) are frequent incidental findings on MRI and associated with future stroke risk in patients without a history of clinically evident cerebrovascular events. However, the prognostic value of CBI in first-ever ischemic stroke patients is unclear and previous studies did not report on different etiological stroke subtypes. We aimed to test CBI phenotypes and their association with stroke recurrence in first-ever ischemic stroke patients according to stroke etiology. Patients and methods: This study is a pooled data analysis of two prospectively collected cohorts of consecutive first-ever ischemic stroke patients admitted to the comprehensive stroke centers of Bern (Switzerland) and Graz (Austria). CBI phenotypes were identified on brain MRI within 72 h after admission. All patients underwent a routine follow-up (median: 12 months) to identify stroke recurrence. Results: Of 1577 consecutive ischemic stroke patients (median age: 71 years), 691 patients showed CBI on brain MRI (44%) and 88 patients had a recurrent ischemic stroke (6%). Baseline CBI were associated with stroke recurrence in multivariable analysis (HR 1.9, 95% CI 1.1–3.3). CBI phenotypes with the highest risk for stroke recurrence were cavitatory CBI in small vessel disease (SVD)-related stroke (HR 7.1, 95% CI 1.6–12.6) and cortical CBI in patients with atrial fibrillation (HR 3.0, 95% CI 1.1–8.1). Discussion and conclusion: This study reports a ≈ 2-fold increased risk for stroke recurrence in first-ever ischemic stroke patients with CBI. The risk of recurrent stroke was highest in patients with cavitatory CBI in SVD-related stroke and cortical CBI in patients with atrial fibrillation. Subject terms: Covert brain infarcts, stroke Graphical abstract

Ljubomir Maksimović: Vizantijski svet i Srbi, Beograd: Istorijski institut, 2008,Studia historica collecta, knjiga 6, 535 str. (Dženan Dautović)   Spomenica akademika Marka Šunjića (1927-1998), ur. Dubravko Lovrenović,Filozofski fakultet u Sarajevu, Sarajevo 2010, 366 str. (Nedim Rabić)

In the past years the interest in Solute Carrier Transporters (SLC) has increased due to their potential as drug targets. At the same time, macrocycles demonstrated promising activities as therapeutic agents. However, the overall macrocycle/SLC‐transporter interaction landscape has not been fully revealed yet. In this study, we present a statistical analysis of macrocycles with measured activity against SLC‐transporter. Using a data mining pipeline based on KNIME retrieved in total 825 bioactivity data points of macrocycles interacting with SLC‐transporter. For further analysis of the SLC inhibitor profiles we developed an interactive KNIME workflow as well as an interactive map of the chemical space coverage utilizing parametric t‐SNE models. The parametric t‐SNE models provide a good discrimination ability among several corresponding SLC subfamilies’ targets. The KNIME workflow, the dataset, and the visualization tool are freely available to the community.