Background To gain insight into the role and relevance of inflammatory and immunological markers in the comprehensive assessment of a patient's immune response to surgical procedures. This study focused on investigating preoperative and postoperative serum levels dynamics of SAA, CRP and proportion of HLA-DR CD14 monocytes, CD14 monocytes, and pro-inflammatory monocytes CD16 T CD14 T in patients who underwent heart surgery using extracorporeal circulation (on-pump). Methods An observational, prospective study was conducted at the Heart Center of the Clinical Center of the University of Sarajevo on 53 patients divided into 3 age groups: 50-59, 60-69, and 70-80. The serum levels of CRP and SAA were quantitatively determined by immunonephelometry. At the same time, flow cytometry technology was applied to measure the proportion of CD14 monocytes, HLA-DR CD14 monocytes, and pro-inflammatory CD16 CD14 monocytes. Results Measured values of CRP; SAA, proportion of monocytes CD14, and proportion of pro-inflammatory monocytes CD16 CD14 are significantly increased postoperatively compared to the preoperative values (p < 0.05). The proportion of HLA-DR CD14 monocytes is lower postoperatively compared to preoperative values (p < 0.001). Furthermore, there are no significant gender differences in the preoperative or postoperative parameters (p > 0.05), with the notable exception of the preoperative proportion of CD14 monocytes (p < 0.05). The analysis of age-related differences indicates no significant changes in the observed preoperative and postoperative parameters among the defined age groups (p >0.05). Conclusions Early monitoring of inflammatory and immunological markers in the postoperative phase could be valuable for healthcare professionals to implement prompt interventions to mitigate negative outcomes.

This research explores how architectural education can be made more practical and relevant to real - world challenges, by identifying strategies that can equip future architects with the skills needed to address pressing social, economic, technological, and environmental issues. It argues that architectural pedagogy should move beyond the idealized, theoretical environment of the studio and engage with the real world and its stakeholders from an early stage in the educational process. The paper examines the introduction and implementation of various practical education models across seven architecture schools within a research pro ject consortium, including higher education institutions in Italy, Norway, Croatia, Montenegro and Bosnia and Herzegovina. The res earch focuses on how practical education is defined in different cultural contexts and what insights can be gained from diverse approaches — varying in scale, complexity, professional engagement, and time spent outside the studio. Using a comparative methodology that includes workshops, site observations, surveys, and interviews, the paper analyses the outcomes of these edu cational practices. The research also presents a "Practice Typology Matrix" as a framework for assessing various models of practice involvement in architectural education, highlighting the most effective approaches for different contexts. Through this analy sis, the paper identifies best practices and strategies for integrating real - world experience into architectural training .

Plasma proteomics technologies are advancing rapidly, offering new opportunities for biomarker discovery and precision medicine. Direct comparisons of available technologies are needed to understand how platform selection affects downstream findings. We compared the performance of a peptide fractionation-based mass spectrometry method (HiRIEF LC-MS/MS) and the Olink Explore 3072 proximity extension assays on 88 plasma samples, analyzing 1129 proteins with both methods. The platforms exhibited complementary proteome coverage, high precision, and concordance in estimating sex differences in protein levels. Quantitative agreement between platforms was moderate (median correlation 0.59, interquartile range 0.33-0.75), mainly influenced by technical factors. Finally, we present a publicly available tool for peptide-level analysis of platform agreement and demonstrate its utility in clarifying cross-platform discrepancies in protein and proteoform measurements. Our findings provide insights for platform selection and study design, and highlight the value of combining mass spectrometry and affinity-based approaches for more comprehensive and reliable plasma proteome profiling. Advancements in plasma proteomics have opened new avenues for biomarker discovery, necessitating a clear understanding of technological capabilities. Here, the authors compare HiRIEF LC-MS/MS and Olink Explore 3072, revealing complementary strengths and moderate quantitative agreement, and introduce PeptAffinity, a resource facilitating detailed peptide-level exploration of differences in protein quantification between platforms.

Many cyberattacks succeed because they exploit flaws at the human level. To address this problem, organizations rely on security awareness programs, which aim to make employees more resilient against social engineering. While some works have, implicitly or explicitly, suggested that such programs should account for contextual relevance, the common praxis in research is to adopt a "general" viewpoint. For instance, instead of focusing on department-specific issues, prior user studies sought to provide organization-wide conclusions by treating all participants equally. Such a protocol may lead to overlooking vulnerabilities that affect only specific subsets of an organization, and which can be (or are) exploited by real-world attackers.In this paper, we tackle such an oversight. First, through a systematic literature review encompassing over 1k papers, we provide factual evidence that prior literature poorly accounted for department-specific needs. Then, building on this (worrying) finding, we carry out a multi-company and mixed-methods study focusing on two pivotal departments of modern organizations: human resources (HR) and accounting. We explore three dimensions: what specific threats are faced by these departments; what topics should be covered in the security-awareness campaigns delivered to these departments; and which delivery methods would maximize the effectiveness of such campaigns for these departments. We begin by interviewing 16 employees of a multinational enterprise, and then use these results as a scaffold to design a structured survey through which we collect the responses of over 90 HR/accounting members of 9 organizations of varying size. We find that HR and accounting departments face distinct threats: HR is targeted through job applications containing mal-ware and executive impersonation, while accounting is exposed to invoice fraud, credential theft, and ransomware. Current training is often viewed as too generic, with employees preferring shorter, scenario-based formats like videos and simulations. These preferences contradict the common industry practice of lengthy, annual sessions. Based on these insights, we propose practical recommendations for designing awareness programs tailored to departmental needs and workflows.

The aviation industry operates as a complex, dynamic system generating vast volumes of data from aircraft sensors, flight schedules, and external sources. Managing this data is critical for mitigating disruptive and costly events such as mechanical failures and flight delays. This paper presents a comprehensive application of predictive analytics and machine learning to enhance aviation safety and operational efficiency. We address two core challenges: predictive maintenance of aircraft engines and forecasting flight delays. For maintenance, we utilise NASA’s C-MAPSS simulation dataset to develop and compare models, including one-dimensional convolutional neural networks (1D CNNs) and long short-term memory networks (LSTMs), for classifying engine health status and predicting the Remaining Useful Life (RUL), achieving classification accuracy up to 97%. For operational efficiency, we analyse historical flight data to build regression models for predicting departure delays, identifying key contributing factors such as airline, origin airport, and scheduled time. Our methodology highlights the critical role of Exploratory Data Analysis (EDA), feature selection, and data preprocessing in managing high-volume, heterogeneous data sources. The results demonstrate the significant potential of integrating these predictive models into aviation Business Intelligence (BI) systems to transition from reactive to proactive decision-making. The study concludes by discussing the integration challenges within existing data architectures and the future potential of these approaches for optimising complex, networked transportation systems.

Diabetes mellitus (DM) and inflammatory bowel disease (IBD) are prevalent chronic conditions characterized by immune dysregulation and metabolic disturbances. The global incidence of both diseases is increasing, with mounting evidence highlighting the critical role of intestinal barrier dysfunction and inflammation in their pathogenesis. Although genome-wide association studies (GWAS) have implicated the orosomucoid-like protein 3 (ORMDL3), also known as ORMDL sphingolipid biosynthesis regulator 3, in susceptibility to both IBD and DM, its precise role in diabetes-associated intestinal alterations remains poorly defined. In this study, we examined intestinal changes in a Sprague Dawley rat model of experimentally induced diabetes, focusing on ORMDL3 expression and its relationship with endoplasmic reticulum (ER) stress and autophagy. Diabetic rats exhibited pronounced histopathological alterations, including villous atrophy, goblet cell depletion, inflammatory cell infiltration, and lipofuscin accumulation, indicative of compromised intestinal barrier integrity and chronic low-grade inflammation. ORMDL3 expression was significantly elevated at both the transcript and protein levels. A strong positive correlation between ORMDL3 and ATF6 suggests the activation of ER stress pathways within the diabetic intestine. Additionally, increased expression of autophagy-related genes, including NOD2, ULK1, and ATG4, was particularly evident in female diabetic rats, indicating a sex-specific modulation of autophagic responses to hyperglycemic stress. The observed molecular and histological changes reflect key mechanisms implicated in IBD, potentially indicating shared pathways driving both diabetic and inflammatory intestinal disorders. Collectively, our findings underscore a complex interplay between hyperglycemia-induced ER stress and autophagy in the diabetic intestine, positioning ORMDL3 as an orchestrator in the underlying pathogenesis and a potential therapeutic target for IBDs.

Cervical cancer is one of the leading causes of cancer in women, worldwide. Infection with humanpapillomavirus (HPV) has been accepted as the primary cause for the development of invasive cervicalcancer and its precursor lesions. Despite HPV infection has been proposed as an indispensable factor forcervical cancer development, only a subset of neoplastic lesions with HPV infection persist and progress toinvasive cancer. This suggests us that other molecular events are also involved in cancer progression. Aimof this study was to extract mRNA from cytobrush-collected healthy and HPV infected cervical epithelialcells and investigate various RNA extraction and purification protocols for assessment of RNA yield andquality. Taking into consideration that cervical cancer screening is based on the cytology basedPapanicolaou test (Pap test), main challenge is to investigate whether the samples obtained by regular Paptesting can be used for gene expression analysis. For this purpose, a total of 68 cervical specimens werepreviously tested for HPV infection. Following HPV testing, samples were submitted to RNA extractionand compared to the products after additional purification step involving DNase I. Products obtained afterdifferent RNA extraction and purification methods were visualized using 2% agarose gel electrophoresis.In conclusion, DNase I based RNA purification represents a necessary step for the assurance of a high-quality extracted RNA used for gene expression analysis studies. Reliance on commercial kits for RNAextraction only, without performing additional purification step can lead to errors in drawing finalconclusions and/or to false negative gene expression profiling, affecting the overall diagnostic procedure.According to obtained results, the type of sampling used in this study was not suitable for the subsequentgene expression analysis.

ABSTRACT Background Trajectories of patients receiving kidney replacement therapy (KRT), including transitions between hemodialysis (HD), peritoneal dialysis (PD) and kidney transplantation (KTx), may vary across patient subgroups and have not yet been investigated in Europe. This study aimed to: (i) describe the number of shifts across KRT modalities; and (ii) characterize the most frequent patient trajectories, including the direction of shifts across KRT modalities, the duration spent on each modality, and patient events, including death. Methods Data of adult patients (≥20 years) who initiated KRT between 2004 and 2013 were extracted from the European Renal Association (ERA) Registry database and patients were followed for 10 years from the moment of KRT initiation. Results were stratified by age, sex, primary renal disease (PRD), country and initial KRT modality. Results Among 289 323 patients, more than two-thirds (69.6%) remained on their initial KRT modality until death or the end of 10 years follow-up, but younger patients and patients who initiated with PD had more shifts across KRT modalities than others. Overall, the most frequent patient trajectories were HD followed by death (53.4%), HD to KTx (10.2%), remaining on HD for 10 years (5.6%), PD followed by death (4.4%) and PD to KTx (2.9%). The most frequent patient trajectories differed between age and PRD groups, and across European countries, but not between women and men. Conclusion The number and direction of shifts across KRT modalities varied by age, PRD, country and initial KRT modality, but not by sex. Future research should further investigate trajectories of patient subgroups that stood out, including young HD patients who died on their initial KRT modality and those who remained on HD for 10 years without undergoing KTx.

High welfare standards for animals used in research is as much an ethical issue as it is a cornerstone of high-quality science. Researchers can improve both animal welfare and data reliability by implementing strategies that reduce stress in experimental animals. One modern and effective approach is to monitor animals within their familiar home-cage environment. Home-cage monitoring (HCM) systems integrate multiple approaches to automatically, continuously, and non-invasively monitor the physiology and behaviour of laboratory animals within their home environments. HCM favours the animals’ natural rhythms and behaviours while reducing stress from various sources and the need for human intervention. In this article, we explore how HCM contributes to the 3Rs framework introduced by Russell and Burch and focus particularly on how to select the most appropriate HCM system for specific research needs. We discuss available resources and practical limitations for system choice, and provide a brief outlook on the evolving role of artificial intelligence to analyse HCM data. We also discuss the opportunities and barriers to HCM adoption, particularly in relation to countries with developing research structure and limited funding in Europe. Our central message is clear: use of HCM technologies supports 3Rs and promotes both better science and better animal welfare. Pametne kletke, večja dobrobit: Podpora načelom 3R v raziskavah na živalih s spremljanjem v domači kletki in ustrezno izbiro sistema Izvleček: Visoki standardi dobrobiti živali v raziskavah niso zgolj etična obveznost, temveč tudi temelj visokokakovostne znanosti. Raziskovalci lahko izboljšajo tako dobrobit živali kot tudi zanesljivost podatkov z uvedbo strategij, ki zmanjšujejo stres pri poskusnih živalih. Eden izmed sodobnih in učinkovitih pristopov je spremljanje živali v njihovem domačem okolju. Sistemi za spremljanje v domači kletki (HCM, angl. home-cage monitoring) združujejo več pristopov za samodejno, neprekinjeno in neinvazivno spremljanje fiziologije in vedenja laboratorijskih živali v njihovem domačem okolju. HCM podpira naravne ritme in vedenja živali ter zmanjšuje stres iz različnih virov in potrebo po posegih človeka. V članku opisujemo, kako HCM prispeva k načelom 3R, ki sta ga uvedla Russell in Burch, s posebnim poudarkom na izbiri najprimernejšega sistema HCM za specifične raziskovalne potrebe. Obravnavamo razpoložljive vire in praktične omejitve pri izviri sistema ter podajamo kratek pogled na razvijajočo se vlogo umetne inteligence pri analizi podatkov HCM. Prispevek obravnava tudi priložnosti in ovire pri uvajanju HCM, zlasti v povezavi z državami z manj razvito raziskovalno infrastrukturo in omejenimi sredstvi v Evropi. Naše osrednje sporočilo je jasno: uporaba tehnologij HCM podpira načela 3R ter spodbuja boljšo dobrobit živali in boljšo znanost. Ključne besede: laboratorijske živali; avtomatsko spremljanje vedenja; izboljšave; kontinuirno zbiranje podatkov; stres

Abstract To preserve resources for future generations and promote rural development, supporting ecotourism is essential. This paper provides guidelines for developing ecotourism, highlighting its role in environmental conservation. While mass tourism benefits rural communities, it can cause significant environmental harm. Therefore, this research promotes ecotourism as a sustainable alternative. In rural areas, ecotourism supports development by responsibly using natural resources. The study focuses on the potential of rural settlements in the Semberija region of Bosnia and Herzegovina, assessing their capacity for ecotourism to aid local development. A decision model was developed, considering four main criteria - natural, infrastructure, socio-cultural, and economic - and their sub-criteria. This model evaluates six rural communities’ ecotourism potential. To determine the importance of each criterion, a fuzzy weighting method with the Bonferroni mean operator was used, revealing economic factors as the most influential. The fuzzy ranking method then ranked the settlements, with Amajlije identified as having the highest ecotourism potential. The findings suggest that promoting ecotourism in Amajlije and similar communities can support sustainable rural development, balancing environmental preservation with economic growth.

Dexketoprofen/tramadol is a fixed-dose multimodal combination analgesic that significantly controls multiple acute pain states, and may have an important clinical application in providing pain control adequate to prevent the transition from acute to chronic postsurgical and low back pain. A consensus is needed to quantify and define the actual burden of postsurgical pain (PSP) and low back pain (LBP), which can support efforts toward effective approaches to manage potential pain chronification. This study utilized a modified Delphi approach. A Scientific Committee set forth 28 statements on six themes about the burden of acute PSP and LBP, their potential transition to chronic pain, their pathophysiology, therapeutic approaches to stop this transition, and the role of multimodal analgesia in this context, specifically a fixed-dose combination oral product of dexketoprofen/tramadol. An international panel of healthcare professionals from various regions and relevant medical specialties participated in a Delphi study and were surveyed for consensus on a 5-point Likert scale with consensus defined as > 70% concordance. A round of online voting lasting 3 months and using an online survey platform was permitted for each participant. A total of 100 experts completed the Delphi survey. All the 28 proposed statements reached consensus > 70% in the first round of voting. A fixed-dose combination product, specifically dexketoprofen/tramadol was recognized as a multimodal analgesic which could effectively relieve acute pain and act to prevent its transition to chronic pain. The high global burden of chronic PSP (CPSP) and chronic LBP (CLBP) was identified as well. Healthcare professionals who deal with pain recognize the burden of acute pain, the risks of acute pain transitioning to chronic pain, and inspire to avert the transition by providing effective multimodal control of acute pain. The role of fixed-dose combination analgesics, in particular dexketoprofen/tramadol, was recognized by consensus as an efficacious and safe therapy option for these acute pain syndromes. 7KDL7wDHZ5GDvGppW1iD89 A Video Abstract is available for this article. To view, please see the online version of the manuscript or follow the ‘Digital Features’ link. A Video Abstract for The Role of Dexketoprofen/Tramadol in Multimodal Therapy to Prevent Acute Postsurgical and Acute Low Back Pain from Developing into Chronic Pain: A Delphi Consensus Study (MP4 112565 KB) A Video Abstract is available for this article. To view, please see the online version of the manuscript or follow the ‘Digital Features’ link. A Video Abstract for The Role of Dexketoprofen/Tramadol in Multimodal Therapy to Prevent Acute Postsurgical and Acute Low Back Pain from Developing into Chronic Pain: A Delphi Consensus Study (MP4 112565 KB)

Clear Cell Sarcoma (CCS) are ultra-rare fusion-translocated soft-tissue tumours occurring mainly in young adults with poor prognosis. Their aggressiveness and resistance to conventional chemotherapy, especially in a metastatic setting, characterize these tumours. A functional drug screen consisting of 80 drugs was performed on patient derived CCS cell lines. Top candidates were validated in 3D cell culture and in vivo models, allowing comparison of drug responses among CCS cell lines, including one matched pair (MUG Lucifer cell lines) representing primary and metastatic disease from the same patient. Underlying mechanisms were evaluated with RNA Seq, fluorescence/luminescence based assays, western blot and IHC. In vitro experiments in CCS spheroids highlighted the transcription inhibitor lurbinectedin to be the best overall candidate which was further confirmed in mouse xenografts, albeit to a lesser extent than observed in vitro, especially in the metastatic CCS model. Transcriptional and functional analyses revealed heterogeneous drug responses and differences in cell death mechanisms across CCS lines, reflecting patient-specific variability. Furthermore, we explored combinational treatment of lurbinectedin with selinexor. Synergistic effects were confirmed in a novel autologous co-culture model incorporating cancer-associated fibroblasts, providing a more physiologically relevant system for drug testing. This study identified promising therapeutic avenues by highlighting key vulnerabilities in CCS, considering both inter tumour heterogeneity, tumour plasticity and the stromal influence on drug response.

Background Acute cholecystitis (AC) is one of the most common surgical emergencies with a wide range of clinical outcomes. Early identification of patients at risk for postoperative complications is essential for optimizing surgical decision-making and resource allocation. Hemogram-derived indices such as the systemic immune-inflammation index (SII) and neutrophil-to-lymphocyte ratio (NLR), in addition to biochemical markers, may provide prognostic value beyond traditional risk factors. Materials and methods This retrospective single-center study included 210 patients admitted to the University Clinical Center Tuzla with AC between January 2024 and January 2025. Demographic, clinical, and laboratory data were collected. Receiver operating characteristic (ROC) analysis was performed to identify optimal cut-off values for predicting complications. Multivariate logistic regression was adjusted for age, sex, diabetes mellitus, hypertension, and other baseline comorbidities, in addition to SII, NLR, glucose, and creatinine. Results Four variables emerged as independent predictors of complications: SII > 950 remained an independent predictor after full adjustment (p = 0.002) with a sensitivity of 78% and specificity of 72%. It yielded the highest discriminatory accuracy among the evaluated markers, with an area under the curve (AUC) of 0.81 (95% confidence interval (CI) 0.75-0.87). No formal comparison with TG18 grading was performed. In contrast, baseline comorbidities such as diabetes mellitus and hypertension did not retain significance after adjustment. Conclusion SII, NLR, glucose, and creatinine independently predicted complications in AC, with SII emerging as the strongest predictor among the evaluated variables. These findings suggest that incorporating hemogram-derived indices into preoperative assessment may enhance risk stratification. However, the retrospective single-center design and potential confounding related to the surgical approach warrant cautious interpretation.