Flow cytometry is a well-established method to analyze cell populations using antibody-based fluorescent detection of protein biomarkers. In this study, we demonstrate the ability to generate intact single cells and perform flow cytometry analysis with two types of formalin fixed tissue: FFPE curls and Representative Samples (RS). RS are homogenized, well-mixed tissue samples from formalin fixed tumors dissected from leftover surgical material. We demonstrate biomarker expression results which correlate with IHC scores. This new method for biomarker quantification may be considered alongside other methods (e.g. digital pathology). Intact single cells were dissociated from RS and FFPE curls using a non-enzymatic, mechanical dissociation method. Cells were stained in suspension for Cytokeratin 8&18 (CK8&18), Ki67, Her2, and DNA content was assessed via DAPI staining and analyzed by flow cytometry. Samples were analyzed on a BD FACSMelody or BD LSR II flow cytometer, and analysis was performed using FCS Express 7 software. Immunohistochemistry (IHC) was performed on the Benchmark ULTRA to compare Ki67 expression (n=78) and Her2 expression (n=16) to the flow analysis. Ki67 expression by IHC was assessed using the international Ki67 working group scoring methods to generate a positive percentage. Her2 expression by IHC was assessed by a pathologist and assigned a score ranging 0 to 3+. Formalin fixed tissue such as RS and FFPE curls can be mechanically dissociated into single cells with intact surface biomarkers. These single cells can be stained in suspension, analyzed via flow cytometry and generate correlating data with both weighted IHC-based scores and clinical IHC scores. The flow analysis of Her2 positive percentage correlates with the IHC scores showing an increasing trend and significant difference between scores for both FFPE and RS. Ki67 expression varied by tumor region using IHC analysis, however by flow cytometry showed a strong correlation with a weighted average across multiregional quantification of Ki67 expression. We demonstrate that millions of intact single cells can be generated from RS and FFPE curls for breast tissue, using non-enzymatic mechanical dissociation methods. Staining in suspension and flow cytometry analysis can be performed in a day for rapid biomarker quantification. Flow cytometry has the potential to analyze FFPE samples using workflows and technologies that have existed in the hematopathology space for decades. Samantha M. Hill, Hannah L. Veloz, Brian Hanley, Tracy Davis, Lisa L. Gallegos, Harold Sasano, Samra Turajlic, Nelson R. Alexander. Optimizing fixed flow cytometry for breast cancer biomarker expression in representative samples and FFPE curls [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 670.

Most human cancers arise from somatic alterations, ranging from single nucleotide variations to structural variations (SVs) that can alter the genomic organization. Pathogenic SVs are identified in various cancer types and subtypes, and they play a crucial role in diagnosis and patient stratification. However, the studies on structural variations have been limited due to biological and computational challenges, including tumor heterogeneity, aneuploidy, and the diverse spectrum of SVs from simpler deletions and focal amplifications to catastrophic events shuffling large fragments from one or multiple chromosomes. Long-read sequencing provides the advantage of improved mappability and direct haplotype phasing. Yet, no tool currently exists to comprehensively analyze complex rearrangements within the cancer genome using long-read sequencing. Here, we present Severus, a tool for somatic SV calling and complex SV characterization using long reads. Severus first detects individual SV junctions from phased split alignments, then constructs a phased breakpoint graph to cluster junctions into complex rearrangement events. We first benchmarked the somatic SV calling performance using six tumor/normal cell line pairs (HCC1395, H1437, H2009, HCC1937, HCC1954, Hs578T). We sequenced all cell lines with Illumina, ONT, and PacBio HiFi. We then established a set of high-confidence calls supported by multiple technologies and tools. Severus consistently had the highest F1 scores compared to the HiFi, ONT, and Illumina methods against this high-confidence SV call set. We then extend our analysis to complex SVs. Severus accurately detected complex events, i.e., chromothripsis and chromoplexy, and templated insertion cycles/chains (TIC), reported for these cell lines. We then compared Severus’ performance with Jabba and Linx, two widely used tools for complex SV calling in short-read sequencing. Our comparison revealed that Severus showed higher agreement with Linx, while Jabba failed to detect most of the SV clusters identified by both Severus and Linx. Severus also outperformed the other tools in characterizing complex reciprocal translocations and TICs. Most of the junctions in complex SVs called by either of the tools but not Severus were either simple SVs with a single long-read junction or were not present in long-read sequencing. In contrast, Severus effectively resolved overlapping SVs by utilizing long-read connectivity, allowing for more accurate clustering of smaller genomic segments. We have also applied Severus to seventeen pediatric leukemia cases. Severus identified two chromoplexy and two cryptic translocations, which were missed by FISH and karyotype panels and were incomplete in Illumina SV calls, further validated by RNA-seq. This highlights the potential of the long-read whole genome sequencing approach for diagnosing complex cases driven by SVs. Ayse Keskus, Asher Bryant, Tanveer Ahmad, Anton Goretsky, Byunggil Yoo, Sergey Aganezov, Ataberk Donmez, Lisa A. Lansdon, Isabel Rodriguez, Jimin Park, Yuelin Liu, Xiwen Cui, Joshua Gardner, Brandy McNulty, Samuel Sacco, Jyoti Shetty, Yongmei Zhao, Bao Tran, Giuseppe Narzisi, Adrienne Helland, Daniel Cook, Pi-Chuan Chang, Alexey Kolesnikov, Andrew Carroll, Erin Molloy, Chengpeng Bi, Adam Walter, Margaret Gibson, Irina Pushel, Erin Guest, Tomi Pastinen, Kishwar Shafin, Karen Miga, Salem Malikic, Chi-Ping Day, Nicolas Robine, Cenk Sahinalp, Michael Dean, Midhat S. Farooqi, Benedict Paten, Mikhail Kolmogorov. Severus: A tool for detecting and characterizing complex structural variants in cancer using long-read sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2848.

Cyber threats have become increasingly prevalent and sophisticated. Prior work has extracted actionable cyber threat intelligence (CTI), such as indicators of compromise, tactics, techniques, and procedures (TTPs), or threat feeds from various sources: open source data (e.g., social networks), internal intelligence (e.g., log data), and “first-hand” communications from cybercriminals (e.g., underground forums, chats, darknet websites). However, “first-hand” data sources remain underutilized because it is difficult to access or scrape their data. In this work, we analyze (i) 6.6 million posts, (ii) 3.4 million messages, and (iii) 120,000 darknet websites. We combine NLP tools to address several challenges in analyzing such data. First, even on dedicated platforms, only some content is CTI-relevant, requiring effective filtering. Second, “first-hand” data can be CTI-relevant from a technical or strategic viewpoint. We demonstrate how to organize content along this distinction. Third, we describe the topics discussed and how “first-hand” data sources differ from each other. According to our filtering, 20% of our sample is CTI-relevant. Most of the CTI-relevant data focuses on strategic rather than technical discussions. Credit card-related crime is the most prevalent topic on darknet websites. On underground forums and chat channels, account and subscription selling is discussed most. Topic diversity is higher on underground forums and chat channels than on darknet websites. Our analyses suggest that different platforms may be used for activities with varying complexity and risks for criminals.

The ubiquity of mobile applications has increased dramatically in recent years, opening up new opportunities for cyber attackers and heightening security concerns in the mobile ecosystem. As a result, researchers and practitioners have intensified their research into improving the security and privacy of mobile applications. At the same time, more and more mobile applications have appeared on the market that address the aforementioned security issues. However, both academia and industry currently lack a comprehensive overview of these mobile security applications for Android and iOS platforms, including their respective use cases and the security information they provide. To address this gap, we systematically collected a total of 410 mobile applications from both the App and Play Store. Then, we identified the 20 most widely utilized mobile security applications on both platforms that were analyzed and classified. Our results show six primary use cases and a wide range of security information provided by these applications, thus supporting the core functionalities for ensuring mobile security.

The widespread deployment of AI systems has led to overlapping concerns around technological impact and governance, often resulting in conceptual ambiguities and policy confusion. We propose a structured and context-sensitive framework for addressing the ethical implications of artificial intelligence. We argue that ethical frameworks must distinguish between the intended domain of AI deployment and the scale of its societal effects.To resolve these tensions, we introduce a two-dimensional matrix based on (1) the extent of AI’s impact and (2) the scope of its governance, which together form four distinct ethical contexts. Within each quadrant, we explore specific risks, values, and regulatory considerations. This matrix not only clarifies the conceptual terrain of AI ethics but also offers a practical roadmap for anticipating ethical risks, developing normative guidance, and informing domain-specific governance strategies.Our goal is not to prescribe a single ethical doctrine but to provide decision-makers with a structured lens through which AI systems can be evaluated in context. This approach promotes adaptive and anticipatory governance while remaining responsive to local, institutional, and cultural variations.

Ethnic villages are examples of tourism products based on historical representations of the region. Within these villages, tourists participate in various customs and traditions, gaining insights into the heritage of local communities. As heritage should be the basis for improving rural tourism, this research was conducted to investigate the extent to which ethnic villages safeguard their heritage. The examination of cultural heritage was carried out by experts who evaluated the importance of the criteria for assessing heritage and the application of cultural heritage in these ethnic villages. A fuzzy approach was used to assess the criteria and ethnic villages using fuzzy Logarithm Methodology of Additive Weights (LMWA) and fuzzy Additive Ratio Assessment (ARAS). The sampling process included an initial pool of 28 ethnic villages identified through various associations and agencies. The villages included in this research were chosen by randomly selecting eight villages using a random number generator. Through collaboration with experts and thorough literature research, 12 criteria were established for evaluating heritage use degree in these villages. Results highlighted tourist participation as the most significant criterion, with the Lubac Valley ethnic village demonstrating superior performance. As this research has shown, applying heritage in tourism provides a unique experience, which is the base for developing rural tourism, and the Lubac Valley could serve as an example to other ethnic villages on building a tourist offer based on heritage. In addition, this research contributes to understanding the current landscape and strengthening the promotion of heritage in ethnic villages by developing a sustainable tourist offer.

BACKGROUND HER2-positive breast cancer (BC) is highly aggressive with a poor prognosis. It is driven by HER2 oncoprotein activation/crosstalk with other receptors like EGFR/(HER1), HER3, and HER4, in addition to IGF-1R, making these receptors ideal therapeutic targets as they are expressed/overexpressed in this subtype. We postulated that targeting HER2 and IGF-1R together is a promising therapy for HER2-positive BC. Thus, we explored the outcome of a novel combination treatment using neratinib, a pan-HER inhibitor, and metformin, an IGF-1R inhibitor, on HER2-positive BC cells. METHODS In this investigation, we used cellular and molecular biology techniques in addition to an angiogenesis model and tissue microarray analysis. RESULTS Our data revealed that this combination therapy significantly reduced cell viability compared to individual treatments and exhibited a synergistic effect in HER2-positive BC cells. Moreover, the combination disrupted cell cycle progression and inhibited colony formation, and invasion of HER2-positive BC cells; this is accompanied by the deregulation of HER1-3 and IGF-1R expression patterns, in addition to Caspase-3, BCL2, Fascin, and Vimentin. Moreover, key regulator molecular pathways, including, ERK1/2, AKT, p38 MAPK, and mTOR, were significantly downregulated upon treatment with neratinib and metformin combination. Additionally, our data pointed out that neratinib and metformin combination inhibited angiogenesis, in-ovo, an important biological event in cancer progression. Finally, using a cohort of 55 HER2-positive BC samples, we revealed that HER2 and IGF-1R are co-expressed in most of the cases. CONCLUSIONS These findings suggest that neratinib and metformin combination can present a promising strategy for targeting multiple pathways in HER2-positive BC.

This article situates itself in the theoretical space between world-systems theory and postcolonial theory, exploring how the state of peripherality and concomitant dependency is reproduced in Bosnia and Herzegovina during the Covid-19 pandemic. The dependent position of the Bosnian protectorate in the world-system, its heritage of colonial rule and peripherality, as well as post-colonial influences of Pax-Americana on state constitution and state capture, have all contributed to the inability of the divided state to adequately respond to the pandemic. This article reveals a multifaceted dependence of Bosnia and Herzegovina on the Western core economies in relation to aid, equipment and vaccines as well as its gradual move towards China as a new opportunity. The pandemic also becomes the stage for competition between the Eastern and Western companies for mining concessions needed to secure the green transition in the respective economies, as a new wave of primitive accumulation ravages the European periphery. As a result of this new scramble for the Balkans, and amidst the global shift towards multipolarity, we see a stable reproduction of peripherality in Bosnia and Herzegovina and the Western Balkans, and re-emergence of ethnic conflict in previously disputed areas, where ethnic groups identify with the interests of their respective hegemons.

Background and aim Public health and social measures (PHSM) are critical aspects of limiting the spread of infections in pandemics. Compliance with PHSM depends on a wide range of factors, including behavioral determinants such as emotional response, trust in institutions or risk perceptions. This study examines self-reported compliance with PHSM during the COVID-19 pandemic in the Federation of Bosnia and Herzegovina (FBIH). Materials and methods We analyze the association between compliance and behavioral determinants, using data from five cross-sectional surveys that were conducted between June 2020 and August 2021 in FBIH. Quota-based sampling ensured that the 1000 people per wave were population representative regarding age, sex, and education level based on the data from the latest census in Bosnia and Herzegovina. One-way analysis of variance (ANOVA) was used to identify significant changes between studies on determinants and PHSM measures. Regression was used to find relations between behavioral determinants and PHSM. Results Participants reported strong emotional responses to the rapid spread of the virus and its proximity to them. Risk perception was spiking in December 2020 when rates of infection and death were particularly high. Trends in policy acceptance were divergent; participants did not rate PHSM as exaggerated, but perceived fairness was low. Trust in institutions was low across all waves and declined for specific institutions such as the health ministry. In five wave-specific regression analyses, emotional response (βmin/max = .11*/.21*), risk perception (βmin/max = .06/.18*), policy acceptance (βmin/max = .09/.20*), and trust in institutions (βmin/max = .06/.21*) emerged as significant predictors of PHSM. Conclusions This study contributes to the body of research on factors influencing compliance with PHSM. It emphasizes the importance of behavioral monitoring through repeated surveys to understand and improve compliance. The study also affirms the impact of public trust on compliance, the risk of eroding compliance over time, and the need for health literacy support to help reinforce protective behaviors.

To examine the impact of obesity on treatment outcomes in inflammatory bowel disease (IBD). Patients aged ≥ 16 years, with IBD, a documented baseline body mass index (BMI), and starting thiopurines and allopurinol, intravenous (iv) vedolizumab, subcutaneous (sc) vedolizumab, ustekinumab, ozanimod, filgotinib, or tofacitinib were selected from the Dutch Initiative on Crohn and Colitis (ICC) registry. Underweight patients (BMI < 18.5 mg/kg2) were excluded. The primary outcome was steroid-free clinical remission (i.e. Simple Clinical Colitis Activity Index (SCCAI) ≤ 2 for ulcerative colitis (UC) and IBD-unclassified (IBD-U), and Harvey Bradshaw Index (HBI) < 5 for Crohn’s disease (CD)) at week 24. Remission rates were compared between normal weight (BMI 18.5–25 kg/m2), and overweight (BMI 25–30 kg/m2), and obese (BMI ≥ 30 kg/m2) patients using binary logistic regression analyses. Multivariable regression analysis was used to correct for possible confounders. Among 1066 patients with IBD, 619 had normal weight, 303 were overweight, and 144 were obese. At week 24, obese patients achieved steroid-free clinical remission less frequently (35.3%, OR = 0.578, 95% CI: 0.380–0.879, p = 0.010), supported by multivariable analysis (OR = 0.537, 95% CI: 0.346–0.832, p = 0.005). Obesity was associated with lower steroid-free clinical remission at week 24. Obese patients with IBD should be encouraged to lose weight not only to improve their overall health, but also to optimize their treatment outcomes.

Inside a closed, thin-walled hollow cylinder, there is a solid state of phase change material (NePCM) that has been nano-enhanced. This NePCM is heated at its bottom, with nanoparticles (Al2O3) inserted and homogenized within the PCM (sodium acetate trihydrate, C2H3O2Na) to create the NePCM. The hollow cylinder is thermally insulated from the outside ambient temperature, while the heat supplied is sufficient to cause a phase change. Once the entire NePCM has converted from a solid to a liquid due to heating, it is then cooled, and the thermal insulation is removed. The cylindrical liquefied NePCM bar is cooled in this manner. Thermal entropy, entransy dissipation rate, and bar efficiency during the heating and cooling of the NePCM bar were analyzed by changing variables. The volume fraction ratio of nanoparticles, inlet heat flux, and liquefied bar height were the variables considered. The results indicate a significant impact on the NePCM bar during liquefaction and convective cooling when the values of these variables are altered. For instance, with an increase in the volume fraction ratio from 3% to 9%, at a constant heat flux of 104 Wm−2 and a liquefied bar height of 0.02 m, the NePCM bar efficiency decreases to 99%. The thermal entropy from heat conduction through the liquefied NePCM bar is significantly lower compared to the thermal entropy from convective air cooling on its surface. The thermal entropy of the liquefied NePCM bar increases on average by 110% without any cooling. With a volume fraction ratio of 6%, there is an 80% increase in heat flux as the bar height increases to 0.02 m.

Background and Objectives Progression independent of relapse activity (PIRA) is associated with worse outcomes in people with multiple sclerosis (pwMS). Although previous research has linked PIRA to accelerated brain and spinal cord atrophy and compartmentalized chronic inflammation, the role of white matter (WM) tract degeneration remains unclear. This study aimed to explore the relationship between PIRA and the integrity of major WM tracts using diffusion tensor imaging (DTI). Methods A cohort of 258 pwMS was stratified based on the presence or absence of PIRA over a 4-year follow-up period. At the end of follow-up, DTI metrics were compared between groups using propensity score–weighted linear regression models to account for potential confounders. Results PwMS with ≥1 PIRA event (n = 39) exhibited significant reductions in fractional anisotropy and increases in radial, axial, and mean diffusivity within the corpus callosum and motor tracts (false discovery rate–adjusted p ≤ 0.04) compared with those without PIRA, indicating more pronounced WM damage. Discussion Our findings highlight an association between PIRA and microstructural damage in key WM tracts. The observed DTI changes likely reflect processes such as Wallerian degeneration and contribute to the growing evidence linking PIRA to neurodegeneration.