Introduction: Classification of genetic variants has significant implications for clinical management. Artificial Intelligence (AI) has the potential to transform classification of genetic variants, such as AlphaMissense, which incorporates structure-function relationships and allele frequencies across large datasets of genetic variants. While this represents a promising new tool, the performance of AlphaMissense has only been compared to known pathogenic and benign variants. Therefore, the discriminatory power for variants of unknown significance (VUS) has yet to be determined. We have performed a comparison of these predictions with variants associated with inherited myeloid neoplasms: 1) to assess the accuracy of these models against VUS; 2) to enhance classification of unpublished VUS by leveraging published information about other variants; and 3) to map the predicted classification onto protein structures to examine spatial patterns. Methods: For 83 genes associated with inherited myeloid diseases, a systematic literature review for missense variants was performed using the Mastermind Genomic Intelligence Platform and ClinVar. We used Alphamissense to characterize VUS missense variants according to predicted pathogenicity scores as pathogenic, ambiguous, or benign. Known pathogenic (n=1594) and benign (n=501) variants served as controls to evaluate the accuracy of the system. AlphaFold2 structures were visualized for structure-function rendering of reclassified VUS and known pathogenic variants to compare and identify discernible patterns of spatial distribution. Results: This variant dataset comprised 1594 pathogenic, 501 benign, and 46676 VUS missense variants. Among VUS, AlphaMissense reclassified a majority of VUS missense mutations and established that the system was 88% accurate in predicting pathogenicity. A higher percentage of variants was classified as pathogenic among tumor suppressor genes e.g. DDX41 and RUNX1 (57.1% and 40.5%) compared to the oncogenes, GATA1 and GATA2 (25.7% and 34.9%). Furthermore, 3D models revealed a majority of variants reclassified to pathogenic were located in regions with defined tertiary structure clustered with known pathogenic variants, while benign variants were located at peripheral positions lacking definite structure. Conclusions: These results demonstrate the discriminatory power of AlphaMissense for VUS pathogenicity prediction for both loss-of-function and gain-of-function disease mechanisms. This work may also have implications for rare or challenging somatic cancer variants and variants in rare diseases. Finally, incorporating information available from empirical and clinical studies for disease-causing variants offers the possibility of significantly enhancing the predictive power of these models. Citation Format: Amina Kurtovic-Kozaric, Asja Campara, Melissa Jahibasic, Amar Mujkic, Adnan Fojnica, Mark J. Kiel. Assessment of AlphaMissense and structure-function predictions demonstrates efficient reclassification of genetic variants of unknown pathogenicity in inherited myeloid neoplasms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2267.

Students in Bosnia and Herzegovina (B&H) score very low on international assessments (TIMSS & PISA), lower than the countries in the region with which it shares similar background. In this paper the characteristics of teachers’ professional development (TPD) in the region of Western Balkan countries (Albania, B&H, Kosovo, Montenegro, North Macedonia, and Serbia) and Croatia are brought into correlation with average results in mathematics and science on TIMSS 2019. Research questions analyze teachers’ attitudes towards their profession and investigate the impact of professional development (PD) of mathematics and science teachers in the last two years, with a specific focus on the situation in B&H, on students’ achievement in mathematics and science. The findings indicate a lack of TPD as a contributing factor to lower results in B&H. The research suggests that B&H should consider reforms in the education system and enhance teachers’ attitudes towards their profession through intensified PD programs to advance education and learning.

Melanoma is the most invasive skin cancer caused by the malignant melanocytes. The use of immune checkpoint blockade (ICB) improved the survival rate in advanced melanoma. Yet, the response rate to ICB varies across patients due to the highly heterogeneous nature of melanoma. Recent studies reported genomic and epigenetic factors contributing to the therapeutic response. Identifying these factors involved in clonal evolution in melanoma is a key to better understanding the tumor progression and divergence in the therapy response. To study melanoma heterogeneity, we generated twenty-four clonal sublines, each derived from a single cell isolated from a parental cell line derived from the M4 mouse melanoma model. DNA prepared from each subline and a spleen from a healthy mouse were subjected to long-read sequencing. Importantly, long-read sequencing allows direct detection of methylation states, small variants, and structural variants in the same run. The results thus provide excellent means to study genetic and epigenetic factors in clonal evolution. Each of these sublines was also implanted in distinct mice for survival and tumor growth analysis and further functional evaluation. We developed Severus, a structural variation (SV) caller for long reads, which works with single (germline), paired (tumor-normal), and multiple samples (e.g., multi-site or time series). Severus takes advantage of improved phasing in long-read sequencing, attributes somatic variants to germline haplotype, and builds a haplotype-specific breakpoint graph that is used to cluster multi-break rearrangements and represent the derived chromosomal structure. We benchmarked Severus using multiplatform validated COLO829 truthset and CHM1/CHM13 haploid genomes, and Severus outperformed all other methods in terms of recall and precision. The structural variation (SV) analysis using Severus with all the sublines showed enrichment of possibly clonal SVs in chr4, chr11, and mainly in chr13. Further investigation revealed SVs in chr13 were not distributed across the chromosome but clustered in certain regions. Analysis of somatic SNVs in chr13 corroborates the localized hypermutation profile, which indicates a possible kataegis. Interestingly, a loss of the chr13 copy affected by kataegis in one of the sublines coincides with a better survival rate, as compared to other sublines, in an allograft melanoma mouse model, which further supports the association between the kataegis and tumor progression. We also identified other clonal and subclonal events, including the homozygous deletion of Cdkn2a in most of the sublines, associated with their aggressiveness in vivo. Our analysis allowed us to identify clonal and subclonal genetic and epigenetic factors involved in tumor progression and evolution in a melanoma model, which can potentially translate to human disease. Citation Format: Ayse Keskus, Anton Goretsky, Yuelin Liu, Xiwen Cui, Tanveer Ahmad, Eva Perez Guijarro, Asher Bryant, Erin Malloy, Salem Malikic, Glenn Merlino, Chi-Ping Day, Cenk Sahinalp, Mikhail Kolmogorov. Melanoma clonal subline analysis reveals genetic factors driving intra-tumor heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7407.

Melanoma is characterized by significant intratumoral heterogeneity and complex evolutionary dynamics. This diversity in genomic alterations leads to the emergence of various subclonal populations within a single tumor. In our research, we established a new model system composed of 24 single-cell-derived clonal sublines (C1-C24), originating from the M4 melanoma model. This model was developed using a genetically engineered hepatocyte growth factor (HGF)-transgenic mouse. We employed Trisicell (Triple-toolkit for single-cell intratumor heterogeneity inference), a cutting-edge computational tool for scalable analysis of intratumor heterogeneity and evaluation based on single-cell RNA mutations. This enabled us to construct a phylogeny tree, revealing melanoma’s intricate branching evolutionary patterns. These patterns show ancestral clones evolving into genetically distinct subclones, which demonstrate varied phenotypic traits such as drug sensitivity or resistance, cellular plasticity, and immunogenicity. In our study, we conducted long-read sequencing on these clonal sublines in the phylogeny and identified structural variants (SVs) using Severus, a tool optimized for phasing in long-read sequencing. The types of SVs we discovered include deletions, insertions, amplifications, translocations, and inversions. We explored their roles in subclonal evolution, particularly focusing on how they disrupt genes and accumulate during melanoma progression. Our initial data from eleven sublines indicated a higher prevalence of ancestral SVs, shared by all sublines, compared to subline-specific SVs, representing later events. Notably, the individual sublines showed a higher rate of gene disruption by SVs, hinting at potential functional selection. Our analysis further revealed that SVs common to all sublines are linked with genes in key cell growth pathways, such as Rap1, Hippo, and calcium signaling pathways. In contrast, subline-specific SVs primarily affect genes involved in neurophysiological pathways, such as glutamatergic synapse and morphine addiction pathways. These findings suggest that different genes, associated with various pathways, are disrupted at distinct stages of melanoma progression, providing insights into the genetic factors that may predispose individual melanocytes to melanomagenesis. This methodology presents a comprehensive tool for characterizing tumor genomes and understanding their relationship with disease progression and therapy resistance. We are continuing our analysis to map SVs across the entire mutation-based phylogeny of all sublines, which will further our understanding of melanoma’s genomic landscape. Citation Format: Xiwen Cui, Ayse G. Keskus, Farid R. Mehrabadi, Salem Malikic, Mikhail Kolmogorov, Chi-Ping Day, Glenn Merlino, S. Cenk Sahinalp. Structural variant dynamics in melanoma: Unraveling tumor heterogeneity and evolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6924.

Microbiome engineering – the targeted manipulation of microbial communities – is considered a promising strategy to restore ecosystems, but experimental support and mechanistic understanding are required. Here, we show that bacterial inoculants for soil microbiome engineering may fail to establish because they inadvertently facilitate growth of native resident microbiomes. By generating soil microcosms in presence or absence of standardized soil resident communities, we show how different nutrient availabilities limit outgrowth of focal bacterial inoculants (three Pseudomonads), and how this might be improved by adding an artificial, inoculant-selective nutrient niche. Through random paired interaction assays in agarose micro-beads, we demonstrate that, in addition to direct competition, inoculants lose competitiveness by facilitating growth of resident soil bacteria. Metatranscriptomics experiments with toluene as selective nutrient niche for the inoculant Pseudomonas veronii indicate that this facilitation is due to loss and uptake of excreted metabolites by resident taxa. Generation of selective nutrient niches for inoculants may help to favor their proliferation for the duration of their intended action while limiting their competitive loss. Bioremediation via microbial inoculation often performs poorly in real-world conditions. Here, the authors show that bacterial inoculants may fail to establish in complex soil microbiomes because they open new niches that facilitate growth of resident microbes.

This study aims to analyze the opinions of Bosnia and Herzegovina (BiH) citizens regarding mandatory pension insurance and the possibility of incorporating private insurance in future reforms. The research involves evaluating the satisfaction of BiH residents with the current pension system, understanding their perception of the pension fund’s risks, and identifying their attitudes towards possible pension system reforms, including the potential involvement of private insurance. The study also seeks to highlight any differences in attitudes towards socio-demographic characteristics, such as gender, employment, length of service, professional qualification, and monthly income. A survey of 812 BiH adults (representative but potentially not fully capturing the entire population) explored these aspects. While acknowledging limitations, the study reveals significant differences in attitudes based on demographics. For example, men are more optimistic about future pensions, while employed individuals are more inclined towards reform. The findings suggest general public support for pension system reform and openness to private insurance. However, the study highlights the need to consider these varying attitudes across different population groups when designing future reforms. This research provides the first quantitative data on BiH residents’ views on private insurance reform, contributing to public discourse and informing future policy changes.

This paper explores the legal regulations on the termination of pregnancy in comparative law, a sensitive topic that, although it does represent the exclusive domain of state regulation, encroaches into human rights as well. The basic research question is how selected modern democratic states legally regulate the issue of the termination of pregnancy. Hence, the research goal is to prove that the trend of modern democratic states is to allow the termination of pregnancy even on request, but also to determine the existence of recent retrograde trends in this area. In this paper and research, except for the comparative method, the analytic, dogmatic, normative, and axiological methods are utilized. Although the core of the research is comparative legal, the historic and international legal segments are presented in short in this paper. In researching the following selected states, BiH, Serbia, Croatia, Germany, USA and Ireland, it is determined that the termination of pregnancy is currently largely allowed even on the request of a pregnant woman, especially for justified reasons, with regards to a specific legal regime (Germany), a sudden shift in complete liberalization (Ireland), and even for retrograde changes towards absolute prohibition (USA). In the argument section, the right of the state to ban a medical procedure out of arbitrary reasons (at least in modern discourse) is considered (even disputed). The conclusion is, considering the practice and development of democratic states, the trend of allowing the termination of pregnancy in early stages on demand of a pregnant woman without a reason, and in later stages with a reason, is evident. Concerning the region, the situation is relative satisfactory, although in greater parts of Bosnia and Herzegovina as well as Croatia the outdated legislation needs innovations, as well as certain improvements, which at this point is inevitable.

Unlike classical artificial neural networks, which require retraining for each new set of parametric inputs, the Deep Operator Network (DeepONet), a lately introduced deep learning framework, approximates linear and nonlinear solution operators by taking parametric functions (infinite-dimensional objects) as inputs and mapping them to complete solution fields. In this paper, two newly devised DeepONet formulations with sequential learning and Residual U-Net (ResUNet) architectures are trained for the first time to simultaneously predict complete thermal and mechanical solution fields under variable loading, loading histories, process parameters, and even variable geometries. Two real-world applications are demonstrated: 1- coupled thermo-mechanical analysis of steel continuous casting with multiple visco-plastic constitutive laws and 2- sequentially coupled direct energy deposition for additive manufacturing. Despite highly challenging spatially variable target stress distributions, DeepONets can infer reasonably accurate full-field temperature and stress solutions several orders of magnitude faster than traditional and highly optimized finite-element analysis (FEA), even when FEA simulations are run on the latest high-performance computing platforms. The proposed DeepONet model's ability to provide field predictions almost instantly for unseen input parameters opens the door for future preliminary evaluation and design optimization of these vital industrial processes.

The targeted use of social robots for the family demands a better understanding of multiple stakeholders’ privacy concerns, including those of parents and children. Through a co-learning workshop which introduced families to the functions and hypothetical use of social robots in the home, we present preliminary evidence from 6 families that exhibits how parents and children have different comfort levels with robots collecting and sharing information across different use contexts. Conversations and booklet answers reveal that parents adopted their child’s decision in scenarios where they expect children to have more agency, such as in cases of homework completion or cleaning up toys, and when children proposed what their parents found to be acceptable reasoning for their decisions. Families expressed relief when they shared the same reasoning when coming to conclusive decisions, signifying an agreement of boundary management between the robot and the family. In cases where parents and children did not agree, they rejected a binary, either-or decision and opted for a third type of response, reflecting skepticism, uncertainty and/or compromise. Our work highlights the benefits of involving parents and children in child- and family-centered research, including parental abilities to provide cognitive scaffolding and personalize hypothetical scenarios for their children.

La cría de caracoles, también conocida como helicicultura, es un tipo de ganadería que implica la reproducción y cultivo de caracoles para consumo humano. Aunque la cría de caracoles sigue siendo relativamente rara en muchas partes del mundo, es una industria en crecimiento que ofrece una serie de beneficios, incluido el impacto ambiental pequeño, alto potencial de beneficios y ventajas nutricionales únicas. Entre varias especies comestibles, los caracoles como Cornu aspersum y Helix pomatia han demostrado un tremendo potencial como fuentes alternativas de proteínas en las dietas animales. Tienen un perfil nutricional favorable, que contiene aminoácidos esenciales, minerales y vitaminas, lo que los convierte en valiosos suplementos o sustitutos de fuentes de proteínas tradicionales. Las técnicas y prácticas de cría de caracoles han avanzado significativamente en los últimos años, lo que ha resultado en un aumento de la productividad y mejoras en los rasgos genéticos en las poblaciones de caracoles. Además, los esfuerzos de investigación en curso están explorando el desarrollo de protocolos de cría de caracoles adaptados a requisitos veterinarios específicos. La optimización de los métodos de cría, incluida la selección artificial, el apareamiento controlado y la mejora genética, tiene un enorme potencial para mejorar los rasgos deseables en las poblaciones de caracoles. Este progreso puede contribuir al desarrollo de razas de caracoles superiores con perfiles nutricionales mejorados, resistencia a enfermedades y propiedades terapéuticas. Además, la cría de caracoles presenta una oportunidad para abordar problemas ecológicos asociados con la producción tradicional de ganado. El uso eficiente de recursos, los requisitos mínimos de espacio y el bajo impacto ambiental hacen que la cría de caracoles sea una alternativa ecológica. Los caracoles también son menos susceptibles a ciertas enfermedades infecciosas que comúnmente afectan a los animales criados tradicionalmente, lo que reduce la necesidad de antimicrobianos y promueve prácticas sostenibles. La educación continua y la investigación sobre técnicas de cría de caracoles, perfiles nutricionales y aplicaciones terapéuticas allanan el camino para prácticas veterinarias innovadoras que priorizan la sostenibilidad, el bienestar animal y mejores resultados de salud. Una mayor investigación en este campo representa una nueva oportunidad para que veterinarios y agricultores contribuyan a la salud y el bienestar de los animales al tiempo que promueven prácticas sostenibles en la industria ganadera. Este artículo de revisión tiene como objetivo proporcionar una visión general de la literatura científica sobre la cría adecuada de caracoles comestibles y los posibles desafíos de los impactos antropogénicos y climáticos negativos como un desafío potencial para los criadores.

Tekst predstavlja prilagođeno izlaganje sa naučne konferencije ZAVNOBiH u retrospektivi: evaluacija historijske važnosti i savremene relevantnosti za društvo i državu koja je organizirana povodom 80. godišnjice od Prvog zasjedanja ZAVNOBiH-a. Konferencija je održana 20. novembra 2023. godine na Univerzitetu u Sarajevu - Fakultetu političkih nauka. The text represents an adapted presentation delivered at the scientific conference ZAVNOBiH in Retrospect – Evaluating Its Historical Importance and Contemporary Relevance for Society and the State, organized on the occasion of marking the 80th Anniversary of the First Session of ZAVNOBiH. The conference was held at the University of Sarajevo - Faculty of Political Sciences, on 20 November 2023.

Working with different DBMS for programmers in their daily work represents a significant challenge in terms of choosing the appropriate way of connecting to the DBMS for the appropriate needs, given that a significant number of factors can influence the same. Although experience is usually one of the important elements that has influence on the selection of the appropriate way to connect to a DBMS, the choice can still vary from system to system and from situation to situation. For this reason, it is necessary to conduct appropriate analysis and research in accordance with various factors that can be an indicator of whether a connection with a DBMS is good or bad. In this research, an analysis was performed between the two leading methods of interaction between Java Spring Boot applications and PostgreSQL databases, namely Spring JDBC and Spring Hibernate. The results of the analysis indicate that there are certain differences in the speed of query execution in certain situations, which Java programmers should pay special attention to when choosing one of the two mentioned technologies to achieve more complex functionalities.

This paper aimed to explore ways to organize Spotify playlists, relying on clustering algorithms. Clustering algorithms were performed on playlists with extracted and standardized audio features obtained from the Spotify API, and the algorithms used were KMeans, DBSCAN, Affinity Propagation, and Spectral Clustering. Their performances were measured with the silhouette score, execution time, and inspection of clustered tracks, where it was determined that KMeans was the best algorithm in this case. Even though the execution time of KMeans is the third best, its silhouette score is the highest with 0.263. With this model, it is possible to effectively perform a mood-based organization of one's Spotify playlist, by dividing it into multiple smaller ones that share similar audio features.