Inflammatory bowel disease (IBD), encompassing Crohn’s disease (CD) and ulcerative colitis (UC), necessitates effective management strategies. This study aims to evaluate the real-world efficacy of vedolizumab, a newer biological therapy, in treating IBD in Bosnia and Herzegovina. A retrospective observational study was conducted across six medical centers, involving 139 IBD patients, 76 with UC and 63 with CD. Patients were assessed for clinical remission and other outcomes at the 26-week mark post vedolizumab treatment initiation. At 26 weeks, clinical remission was achieved in 82.9% of UC patients and 85.7% of CD patients. Mucosal healing was observed in 38.1% of CD patients. The efficacy of vedolizumab did not significantly differ based on prior anti-tumor necrosis factor (anti-TNF) exposure. Notably, the clinical scoring tools for predicting vedolizumab response showed limited applicability in this cohort. Vedolizumab demonstrated high efficacy in treating both UC and CD in real-world settings in Bosnia and Herzegovina, underscoring its potential as a significant therapeutic option in IBD management.

Simple Summary The manual measurement of ablation zones (AZs) in radiofrequency ablation (RFA) therapy is prone to inaccuracies, highlighting the need for automated methods. Our study investigated the effectiveness of an Artificial Intelligence (AI) model, Mask2Former, in automating AZ measurements from ultrasound images, comparing its performance against manual techniques. Conducted on chicken breast and liver samples, the study found the AI model to achieve high accuracy, particularly in chicken breast tissue, with no significant difference in measurements between AI and manual methods. These results suggest that the Mask2Former model can significantly reduce variability in manual measurements, marking a step forward in the automation of AZ measurement in RFA therapy research and potentially improving the precision of treatment assessments. Abstract Background: The accurate delineation of ablation zones (AZs) is crucial for assessing radiofrequency ablation (RFA) therapy’s efficacy. Manual measurement, the current standard, is subject to variability and potential inaccuracies. Aim: This study aims to assess the effectiveness of Artificial Intelligence (AI) in automating AZ measurements in ultrasound images and compare its accuracy with manual measurements in ultrasound images. Methods: An in vitro study was conducted using chicken breast and liver samples subjected to bipolar RFA. Ultrasound images were captured every 15 s, with the AI model Mask2Former trained for AZ segmentation. The measurements were compared across all methods, focusing on short-axis (SA) metrics. Results: We performed 308 RFA procedures, generating 7275 ultrasound images across liver and chicken breast tissues. Manual and AI measurement comparisons for ablation zone diameters revealed no significant differences, with correlation coefficients exceeding 0.96 in both tissues (p < 0.001). Bland–Altman plots and a Deming regression analysis demonstrated a very close alignment between AI predictions and manual measurements, with the average difference between the two methods being −0.259 and −0.243 mm, for bovine liver and chicken breast tissue, respectively. Conclusion: The study validates the Mask2Former model as a promising tool for automating AZ measurement in RFA research, offering a significant step towards reducing manual measurement variability.

Survivors of colorectal cancer (CRC) are at risk of developing another primary colorectal cancer - metachronous CRC. Understanding which pathological features of the first tumour are associated with risk of metachronous CRC might help tailor existing surveillance guidelines. Population-based CRC cases were recruited from the United States, Canada and Australia between 1997 and 2012 and followed prospectively until 2022 by the Colon Cancer Family Registry. Metachronous CRC was defined as a new primary CRC diagnosed at least 1 year after the initial CRC. Those with the genetic cancer predisposition Lynch syndrome or MUTYH mutation carriers were excluded. Cox regression models were fitted to estimate hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) for the associations. Of 6085 CRC cases, 138 (2.3%) were diagnosed with a metachronous CRC over a median follow-up time of 12 years (incidence: 2.0 per 1000 person-years). CRC cases with a synchronous CRC were 3.4-fold more likely to develop a metachronous CRC (adjusted HR: 3.36, 95% CI: 1.89-5.98) than those without a synchronous tumour. CRC cases with MMR-deficient tumours had a 72% increased risk of metachronous CRC (adjusted HR: 1.72, 95% CI: 1.11-2.64) compared to those with MMR-proficient tumours. Compared to cases who had an adenocarcinoma histologic type, those with an undifferentiated histologic type were 77% less likely to develop a metachronous CRC (adjusted HR: 0.23, 95% CI: 0.06-0.94). Existing surveillance guidelines for CRC survivors could be updated to include increased surveillance for those whose first CRC was diagnosed with a synchronous CRC or was MMR-deficient.

Oncologic treatment has recently undergone substantial therapeutic paradigm shifts, from classical tumor-specific and biomarker-agnostic approaches to more molecular, biomarker-specific, and tumor-agnostic. Tumor-type (histology) agnostic drugs work across cancer types and present a novel shift in precision oncology. Compared with traditional cancer therapies, this novel approach implies molecularly informed treatment strategies and enables targeted treatment regardless of tumor histology (type). Such drugs are usually utilized in small clinical cohorts with diverse tumor types sharing a common genomic event (molecular biomarker). One of the key elements of this approach is the presence of a common biomarker across many tumor types. Biomarker predicts response to the targeted drugs, as well as deciphers potential resistance mechanisms. Read more in the PDF.

This study explores the impact of digit(al)isation and convergence on television in Bosnia and Herzegovina, considering the fact that the digital revolution, sparked by the proliferation of advanced digital technologies, has brought significant changes to the media sphere. One of the key phenomena in contemporary media is media convergence, a multi-meaning concept influencing various stakeholders in the media landscape – media owners, management, journalists, editors, advertisers, and audiences. Qualitative research was conducted in this study, through semi-structured in-depth interviews (N=27) with management, journalists, and editors from Bosnian Herzegovinian TV stations (N=15). The aim of the study is to understand how media professionals navigate digital/convergent circumstances and which advantages and challenges they identify. Based on this research, it can be concluded that media professionals recognise the significance of quality content in the media (irrespective of technological changes), as well as the importance of collaborative effort that underscores shared responsibility to uphold standards and excellence within the dynamic digital media landscape.

ABSTRACT

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The study aims to examine the causality link between Greenfield Investments, Regulatory Quality, and Economic Growth by using seven Western Balkan countries between 2003 and 2022. Johansen cointegration tests, the VECM model, and multiple empirical unit root tests are the foundation of the empirical analysis. The study's findings indicate that, in the short run, GFI-led growth in Albania and North Macedonia is supported. In the long run, the analysis backs the growth driven by GFI in Serbia and Montenegro and the growth driven by regulatory quality in Albania, Bosnia and Herzegovina, North Macedonia, Serbia, Montenegro, and Bulgaria. The findings support the growth driven by regulatory quality in most Western Balkan countries, reassuring national policymakers that encouraging improvements in regulatory quality and GFI inflows is warranted and will ultimately spur economic growth.

Building on previous work, this paper extends the modeling of political structures from simplicial complexes to hypergraphs. This allows the analysis of more complex political dynamics where agents who are willing to form coalitions contain subsets that would not necessarily form coalitions themselves. We extend topological constructions such as wedge, cone, and collapse from simplicial complexes to hypergraphs and use them to study mergers, mediators, and power delegation in political structures. Concepts such as agent viability and system stability are generalized to the hypergraph context, alongside the introduction of the notion of local viability. Additionally, we use embedded homology of hypergraphs to analyze power concentration within political systems. Along the way, we introduce some new notions within the hypergraph framework that are of independent interest.

Background: A subset of developmental disorders (DD) is characterized by disease-specific genome-wide methylation changes. These episignatures inform about underlying pathogenic mechanisms and can be used to assess the pathogenicity of genomic variants as well as confirm clinical diagnoses. Currently, episignature detection requires the use of indirect methylation profiling microarrays. We hypothesized that long-read whole genome sequencing would not only enable the detection of single nucleotide variants and structural variants but also episignatures. Methods: Genome-wide nanopore sequencing was performed in forty controls and twenty patients with confirmed or suspected episignature-associated DD, representing thirteen distinct diseases. Following variant and methylome calling, hierarchical clustering and dimensional reduction were used to determine the compatibility with microarray-based episignatures. Subsequently, we developed a support vector machine for each DD. Results: Nanopore sequencing based methylome patterns were concordant with microarray-based episignatures. Our classifier identified episignatures in 17/20 disease samples and none in the control samples. The remaining three patient samples were classified as controls by both our classifier and a commercial microarray assay. In addition, we identified all underlying pathogenic single nucleotide and structural variants and showed haplotype-aware skewed X-inactivation evaluation directs clinical interpretation. Conclusion: This proof-of-concept study demonstrates nanopore sequencing enables concurrent haplotyped genomic and epigenomic analyses.

This Letter reports the device and material investigations of enhancement-mode p-GaN-gate AlGaN/GaN high electron mobility transistors (HEMTs) for Venus exploration and other harsh environment applications. The GaN transistor in this work was subjected to prolonged exposure (11 days) in a simulated Venus environment (460 °C, 94 bar, complete chemical environment including CO2/N2/SO2). The mechanisms affecting the transistor performance and structural integrity in harsh environment were analyzed using a variety of experimental, simulation, and modeling techniques, including in situ electrical measurement (e.g., burn-in) and advanced microscopy (e.g., structural deformation). Through transistor, Transmission Line Method (TLM), and Hall-effect measurements vs temperature, it is revealed that the mobility decrease is the primary cause of reduction of on-state performance of this GaN transistor at high temperature. Material analysis of the device under test (DUT) confirmed the absence of foreign elements from the Venus atmosphere. No inter-diffusion of the elements (including the gate metal) was observed. The insights of this work are broadly applicable to the future design, fabrication, and deployment of robust III-N devices for harsh environment operation.

Aim: This study aimed to identify and analyze the top 100 most cited digital health and mobile health (m-health) publications. It could aid researchers in the identification of promising new research avenues, additionally supporting the establishment of international scientific collaboration between interdisciplinary research groups with demonstrated achievements in the area of interest. Methods: On 30th August, 2023, the Web of Science Core Collection (WOSCC) electronic database was queried to identify the top 100 most cited digital health papers with a comprehensive search string. From the initial search, 106 papers were identified. After screening for relevance, six papers were excluded, resulting in the final list of the top 100 papers. The basic bibliographic data was directly extracted from WOSCC using its “Analyze” and “Create Citation Report” functions. The complete records of the top 100 papers were downloaded and imported into a bibliometric software called VOSviewer (version 1.6.19) to generate an author keyword map and author collaboration map. Results: The top 100 papers on digital health received a total of 49,653 citations. Over half of them (n = 55) were published during 2013–2017. Among these 100 papers, 59 were original articles, 36 were reviews, 4 were editorial materials, and 1 was a proceeding paper. All papers were written in English. The University of London and the University of California system were the most represented affiliations. The USA and the UK were the most represented countries. The Journal of Medical Internet Research was the most represented journal. Several diseases and health conditions were identified as a focus of these works, including anxiety, depression, diabetes mellitus, cardiovascular diseases, and coronavirus disease 2019 (COVID-19). Conclusions: The findings underscore key areas of focus in the field and prominent contributors, providing a roadmap for future research in digital and m-health.

This paper investigates an autonomous discrete-time glycolytic oscillator model with a unique positive equilibrium point which exhibits chaos in the sense of Li–Yorke in a certain region of the parameters. We use Marotto’s theorem to prove the existence of chaos by finding a snap-back repeller. The illustration of the results is presented by using numerical simulations.

Aim of study: A two-year experiment (2021-2022) was conducted to assess the response of a local maize hybrid BL-43 to different water regimes (full irrigation, deficit irrigation and rainfed) at two distinguished pedo-climatic locations (Aleksandrovac and Butmir) in Bosnia and Herzegovina (BiH). Area of study: The field experiment was located in Aleksandrovac (near Banja Luka) and Butmir (near Sarajevo) in BiH. Material and methods: A randomized block design was adopted at both experimental locations with three replicates. An Excel-based irrigation tool was used to manage crop water requirements and irrigation scheduling. Main results: Crop response to water was affected by site-specific agronomic management, the duration of phenological stages and their interconnection with precipitation events. At both locations, the effect of the water inputs on grain yield was statistically significant confirming the beneficial impact of irrigation. The effect of water stress on yield was particularly pronounced at Aleksandrovac, which was under water and temperature stresses during flowering time. During both seasons and for all water regimes, the total average grain yield was greater at Butmir than at Aleksandrovac for 38% and 27%, respectively. Research highlights: This is the first experimental study conducted in BiH on the effect of irrigation on maize grain production under different pedoclimatic conditions. The study emphasizes the need for knowledge regarding the impacts that climate change is having on the productivity of one of the region's most important crops.