The purpose of this study was to evaluate the spatiotemporal immunoexpression pattern of microtubule-associated protein 1 light chain 3 beta (LC3B), glucose-regulated protein 78 (GRP78), heat shock protein 70 (HSP70), and lysosomal-associated membrane protein 2A (LAMP2A) in normal human fetal kidney development (CTRL) and kidneys affected with congenital anomalies of the kidney and urinary tract (CAKUT). Human fetal kidneys (control, horseshoe, dysplastic, duplex, and hypoplastic) from the 18th to the 38th developmental week underwent epifluorescence microscopy analysis after being stained with antibodies. Immunoreactivity was quantified in various kidney structures, and expression dynamics were examined using linear and nonlinear regression modeling. The punctate expression of LC3B was observed mainly in tubules and glomerular cells, with dysplastic kidneys displaying distinct staining patterns. In the control group’s glomeruli, LAMP2A showed a sporadic, punctate signal; in contrast to other phenotypes, duplex kidneys showed significantly stronger expression in convoluted tubules. GRP78 had a weaker expression in CAKUT kidneys, especially hypoplastic ones, while normal kidneys exhibited punctate staining of convoluted tubules and glomeruli. HSP70 staining varied among phenotypes, with dysplastic and hypoplastic kidneys exhibiting stronger staining compared to controls. Expression dynamics varied among observed autophagy markers and phenotypes, indicating their potential roles in normal and dysfunctional kidney development.

Machine Learning-based heuristics have recently shown impressive performance in solving a variety of hard combinatorial optimization problems (COPs). However they generally rely on a separate neural model, specialized and trained for each single problem. Any variation of a problem requires adjustment of its model and re-training from scratch. In this paper, we propose GOAL (for Generalist combinatorial Optimization Agent Learning), a generalist model capable of efficiently solving multiple COPs and which can be fine-tuned to solve new COPs. GOAL consists of a single backbone plus light-weight problem-specific adapters for input and output processing. The backbone is based on a new form of mixed-attention blocks which allows to handle problems defined on graphs with arbitrary combinations of node, edge and instance-level features. Additionally, problems which involve heterogeneous types of nodes or edges are handled through a novel multi-type transformer architecture, where the attention blocks are duplicated to attend the meaningful combinations of types while relying on the same shared parameters. We train GOAL on a set of routing, scheduling and classic graph problems and show that it is only slightly inferior to the specialized baselines while being the first multi-task model that solves a wide range of COPs. Finally we showcase the strong transfer learning capacity of GOAL by fine-tuning it on several new problems. Our code is available at https://github.com/naver/goal-co/.

Human mitochondrial genes MT-ATP6 and MT-ATP8 encode the subunits 6 and 8, respectively, of ATP synthase, a vital protein Complex V intricately involved in oxidative phosphorylation and ATP metabolism. This enzyme produces ATP from ADP in the mitochondrial matrix utilizing energy provided by the proton electrochemical gradient. Pathogenic mutations within these genes have been linked to various syndromes such as NARP syndrome, Leigh syndrome, mitochondrial myopathy with reversible cytochrome C oxidase deficiency, and progressive spastic paraparesis, among others. In our investigation, we sequenced 24 complete human mitochondrial genomes of healthy adult individuals from Bosnia and Herzegovina, each representing unique maternal lineage. Employing the Illumina MiSeq NGS platform and the Nextera XT DNA library preparation protocol, we obtained raw NGS reads. Subsequent analysis utilizing SAMtools enabled the identification of genetic variants within the MT-ATP6 and MT-ATP8 genes. We identified a total of 11 SNPs, including three in MT-ATP8 and eight in MT-ATP6, with none of them being associated with any mitochondrial diseases or conditions. Our results align well with previously reported genome variation data for European populations and set the groundwork for future mtDNA analysis for clinical purposes in Bosnia and Herzegovina.

Sport, particularly in the realm of professional competition, is a domain of human endeavor that is increasingly dependent on the use of analytical statistical information. Consequently, mathematics and statistics are becoming increasingly crucial elements in sports. Although experts recognize the importance of analytics in women’s basketball, the literature addressing this subject remains limited. The objective of this study is to employ quantitative methodologies to discover prevailing patterns in global women’s basketball representation. The entities examined in this article were the games contested during the 2021 Olympic Games, the 2022 World Cup, and the 2023 continental championships. Two regression models were created for the research, using thirteen standard variables observed in the game. The evaluation of the regression model was conducted using the stepwise regression method, incorporating dimensionality reduction based on the outcomes of factor analysis. Among the 14 models that were observed, 13 of them exhibited strong and moderate linkages, while only 1 displayed weak connections and lacked statistical significance. The primary factors that account for the disparity between winning and losing teams in games are primarily associated with shooting accuracy toward the basket. When examining individual championships, the percentage surpassed 50% in all cases except for AfroBasket. However, when considering the overall results, the significance of shooting rose to 86%. The variable representing offensive rebound efficiency had a significant influence on the outcome, being present in all individual competitions, whereas defensive rebound efficiency was only considered in the overall results.

Chickpea and lentils are one of the most important legumes not only as sources of food and nutrients but also for enrichment of soil as a nitrogen fixating crop. An early onset of higher temperatures and drought are affecting chickpea and lentil growth and flowering leading to reduction of yield. In search for a tolerant varieties presented study performed a large-scale screening of two legume varieties (chickpea and lentils) investigating phenotypical response to early onset of drought under heat stress. Under heat stress and two different irrigation conditions, 19 chickpea and 18 lentil accessions were examined. The evaluation focused on their growth, biomass production, and flowering rate in comparison to commercially available varieties. Six chickpea accessions showed tolerance to water stress while only two lentil accessions differed from the rest of tested accessions. Generally, lentils genotypes were less stressed by decreased water availability compared to chickpea. Large scale screening of legume accessions could be a valuable tool to identify new varieties that could show phenotypical traits more adaptable to climate related environmental stresses. To improve the reproductive efficiency in chickpeas and lentils under adverse conditions associated to climate change an extensive breeding effort should be focused on investigation of more tolerant genotypes and cultivation in crop systems.

Quantum entanglement is so fundamentally different from a network packet that several quantum network stacks have been proposed; one of which has even been experimentally demonstrated. Several simulators have also been developed to make up for limited hardware availability, and which facilitate the design and evaluation of quantum network protocols. However, the lack of shared tooling and community-agreed node architectures has resulted in protocol implementations that are tightly coupled to their simulators. Besides limiting their reusability between different simulators, it also makes building upon prior results and simulations difficult. To address this problem, we have developed QuIP: a P4-based Quantum Internet Protocol prototyping framework for quantum network protocol design. QuIP is a framework for designing and implementing quantum network protocols in a platform-agnostic fashion. It achieves this by providing the means to flexibly, but rigorously, define device architectures against which quantum network protocols can be implemented in the network programming language $\text{P}4_{16}$ . QuIP also comes with the necessary tooling to enable their execution in existing quantum network simulators. We demonstrate its use by showcasing V1Quantum, a completely new device architecture, implementing a link- and network-layer protocol, and simulating it in the existing simulator NetSquid.

The aim of this study was to select the best marketing communication channel for a medium-sized agricultural company in the area of the city of Bijeljina by applying multi-criteria decision-making methods. Eight criteria were used for the research, and five communication channels were selected. The research on the importance of individual criteria was influenced by the commercial management of the company in question with their common attitude, i.e. assessment. The Entropy - MABAC method of multi-criteria decision-making was used for the methodology. The results show that the criterion of diversity of new information is the most significant. The best-rated communication channel is the company’s good image. The second-best rated alternative is the use of the internet, specifically social media. The results provide a good basis for further research in this area with the aim of determining the factors that influence the choice of future promotion methods and obtaining useful information.

Numerous archaeological sites in Bosnia and Herzegovina represent a historical heritage and testify to the rich cultural, social, and political life of medieval Bosnia. Bobovac, the capital of the Bosnian Kingdom after King Tvrtko I's coronation in 1377, featured a royal complex with a palace, church, and fortification. Recent molecular-genetic research on skeletal remains from Bobovac aims to uncover medieval ancestors' customs and genetic origins. Fifteen well-preserved teeth samples from Bobovac were processed. STR amplification employed PowerPlex® Fusion and Investigator® 24plex QS Kits, with Y-STR profiles generated using the PowerPlex® Y23 System. Fourteen partial autosomal STR profiles were obtained, enabling sex determination and kinship analysis. STR amplification success varied due to ancient DNA degradation, with larger loci showing lower amplification rates. Kinship analysis confirmed appropriate marker selection, demonstrating high reliability for determining close relationships. Integrating aDNA analysis with archaeological research enhances our understanding of historical populations, connecting archaeology and forensic genetics to contribute to the broader narrative of human history.

COVID-19 pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), was declared in 2020 by the World Health Organization. New mutations have been identified, leading to various variants of this virus, including Alpha, Beta, Gamma, Delta, and Omicron, which are classified as variants of concern (VOCs) and have raised considerable concerns for global public health. Such constant spread and changes in the genome of the virus require continuous monitoring. This research focuses on the evolution of SARS-CoV-2 through a detailed presentation of the viral genome, protein structure and interpretation, with the presentation of phylogenetic characteristics and patterns. We obtained the sequence data from the European region focusing on the S, E, and RdRp proteins from the publicly available NCBI database. We next used the MEGA11 package to generate the multiple sequence alignments and create phylogenetic trees. The SWISS-MODEL server was connected to the Protein Data Bank to obtained tertiary structure images of all the proteins presented in the paper. Stability studies of obtained mutations were performed via MUpro online tool. The results indicate a substantial impact of the Omicron variant relative to others, particularly concerning the alterations and mutations observed in the spike (S) protein, which is crucial in the infection process.

Purpose. The aim of the study was to examine the effects of five weeks detraining period on body composition changes in elite professional Indonesian male soccer players. Material and methods. The body composition of 24 top-level male soccer players (age: 26.33 ± 4.06 years) competing in First League of Indonesia was measured before and after the 5-weeks detraining period. Body composition variables, including body mass, body fat percentage, fat-free mass, and total body water percentage, were measured using the bioelectrical impedance method. The results. The paired samples T-test showed significant changes in the means of body composition variables for body fat percentage, fat-free mass, and total body water percentage. Mean values for body fat percentage increased during the detraining period from 10.87 ± 2.47% to 11.98 ± 2.75% (10.3%). A decrease in mean values for fat-free mass (61.34 ± 5.74 kg to 59.80 ± 6.22; 2.49%) and total body water percentage (from 65.13 ± 1.84% to 64.40 ± 1.99%; 1.12%) was observed. No significant changes occurred in body mass (from 69.05 ± 8.07 kg to 69.05 ± 8.48 kg; 0.04%) from initial to final testing. Conclusions. Since there was a significant difference in body fat percentage, fat-free mass, and total body water percentage% before and after detraining period., it is suggested that 5 weeks of detraining period.  for the professional soccer players may not be necessary, and the duration should be shortened to maintain body composition status.

We introduce Mathador-LM, a new benchmark for evaluating the mathematical reasoning on large language models (LLMs), combining ruleset interpretation, planning, and problem-solving. This benchmark is inspired by the Mathador game, where the objective is to reach a target number using basic arithmetic operations on a given set of base numbers, following a simple set of rules. We show that, across leading LLMs, we obtain stable average performance while generating benchmark instances \emph{dynamically}, following a target difficulty level. Thus, our benchmark alleviates concerns about test-set leakage into training data, an issue that often undermines popular benchmarks. Additionally, we conduct a comprehensive evaluation of both open and closed-source state-of-the-art LLMs on Mathador-LM. Our findings reveal that contemporary models struggle with Mathador-LM, scoring significantly lower than average 3rd graders. This stands in stark contrast to their strong performance on popular mathematical reasoning benchmarks. The implementation of Mathador-LM benchmark is available at \href{https://github.com/IST-DASLab/Mathador-LM}{github.com/IST-DASLab/Mathador-LM}.

BACKGROUND In 2020, the COVID-19 pandemic caused disruptions in kidney replacement therapy (KRT) services worldwide. The aim of this study was to assess the effect of the COVID-19 pandemic in 2020 on the incidence of KRT, kidney transplantation activity, mortality and prevalence of KRT across Europe. METHODS Patients receiving KRT were included from 17 countries providing data to the European Renal Association Registry. The epidemiology of KRT in 2020 was compared with average data from the period 2017-2019. Also changes occurring during the first and second wave of the pandemic were explored. RESULTS The incidence of KRT was 6.2% lower in 2020 compared with 2017-2019, with the lowest point (-22.7%) during the first wave in April. The decrease varied across countries, was smaller in males (-5.2%) than in females (-8.2%), and was moderate for peritoneal dialysis (-3.7%) and haemodialysis (-5.4%), but substantial for pre-emptive kidney transplantation (-23.6%). The kidney transplantation rate decreased by 22.5%, reaching a nadir of -80.1% during the first wave, and most for living donor kidney transplants (-30.5%). While in most countries the kidney transplantation rate decreased, in the Nordic/Baltic countries and Greece there was no clear decline. In dialysis patients, mortality increased by 11.4%, and was highest in those aged 65-74 years (16.1%), in those with diabetes as primary renal disease (15.1%), and in those on haemodialysis (12.4%). In transplant recipients, the mortality was 25.8% higher, but there were no subgroups that stood out. In contrast to the rising prevalence of KRT observed over the past decades across Europe, the prevalence at the end of 2020 (N=317787) resembled that of 2019 (N=317077). CONCLUSION The COVID-19 pandemic has had a substantial impact on the incidence of KRT, kidney transplant activity, mortality of KRT, and prevalence of KRT in Europe with variations across countries.