Digital technologies have altered the material conditions of mathematics teaching, but the extent to which they have transformed pedagogy is more contested than the spread of devices and platforms implies. This critical narrative review examines the methodological transition from board-centred exposition to dynamic, interactive, blended, adaptive and artificial-intelligence-supported mathematics teaching. The review integrates evidence from mathematics education, educational technology and teacher-learning research, with particular attention to what changes in mathematical activity, classroom interaction, feedback, assessment, learning space and teacher decision-making when digital resources are introduced. Evidence was selected through structured searches of accessible scholarly sources, citation chaining and verification of bibliographic metadata and Digital Object Identifiers, with the main search period extending from 2000 to 14 June 2026 and earlier work retained when conceptually necessary. Across meta-analyses and classroom studies, digital technology is associated with generally positive but heterogeneous effects on achievement. Benefits are strongest when technology performs a clear didactical function, such as supporting multiple representations, conjecture testing, problem solving, communication, adaptive feedback or deliberate redistribution of class time. By contrast, hardware or software adoption can leave instructional methodology largely unchanged, as illustrated by interactive whiteboards used primarily as enlarged presentation surfaces. Teacher knowledge, task design, orchestration, professional learning and alignment between technology and mathematical goals repeatedly moderate outcomes. Blended and flipped designs can increase active class time, yet evidence on durability and transfer remains limited. Intelligent tutoring systems and learning analytics extend adaptive and diagnostic possibilities, while generative artificial intelligence adds flexible explanation and content generation alongside material risks of mathematical error, overreliance and assessment ambiguity. The review concludes that the digital transformation of mathematics teaching is best understood as conditional pedagogical reconfiguration rather than technological substitution. Research now needs longer-term, mechanism-focused and equity-sensitive designs that distinguish the contribution of tools from the contribution of the teaching practices built around them.

This study aims to develop a novel Multi Criteria Decision Making (MCDM) methodological model for use as a decision support tool in industrial machine selection problems. To this end, a new integrated MCDM model consisting of Logarithmic normalization and Standard Deviation (LOGSTA), Logarithmic Percentage Change-driven Objective Weighting (LOPCOW), Logarithmic Decomposition of Criteria Importance (LODECI), and Evaluation by Distance from Ideal Solution of Alternatives (EDISA) methods has been designed for a real-world lathe selection problem faced by a manufacturing company in Turkiye. The criterion weights obtained according to the three methods (LOGSTA, LOPCOW, and LODECI) were combined, and the combined criterion weights were transferred to the EDISA method to create an alternative lathe ranking. According to the combined criterion weights, the criterion with the highest importance level was failure frequency (C1), while the criterion with the lowest importance level was active working time (C5). According to the ranking obtained as a result of transferring the combined criterion weights to the EDISA method, the lathe with the highest performance was determined to be Doosan PUMA VT 900 (A2), while the lathe with the lowest performance was determined to be Doosan Puma 300 LM (A1). The comparison analysis shows that the EDISA method produces the same rankings as the ARAS, COPRAS, and RAWEC methods. It is believed that this framework enables manufacturing managers to compare acquisition cost, reliability, operating characteristics, and resale value within a transparent decision process.

Background: Rosuvastatin, a potent lipid-lowering statin, and curcumin, a bioactive naturally occurring polyphenolic phytochemical, both show pleiotropic antioxidant and anti-inflammatory properties. In addition, curcumin shows also antimicrobial, anticancer, hypolipidemic and antifibrotic effects. From the pharmacodynamic point, rosuvastatin and curcumin target overlapping molecular pathways—suggesting possible pharmacodynamic synergy that has emerged as a promising therapeutic approach in the management of various diseases, including cardiovascular, metabolic, kidney, and inflammatory diseases. Objectives: This review aimed to systematically summarize and critically evaluate all available preclinical data concerning the combined use of rosuvastatin and curcumin, emphasizing their possible synergistic effects. Methods: A total of seven preclinical studies that investigated the combination of curcumin and rosuvastatin, three in vitro and four in vivo, conducted between 2017 and 2025, were included in the analysis. Results: While in vitro studies suggested a promising synergy in lipid-lowering, antioxidant, and anti-inflammatory effects, in vivo findings confirmed enhanced lipid-lowering effects, potential hepatoprotection and nephroprotection when two agents are co-administered. In addition to pharmacodynamic interaction, pharmacokinetic studies also revealed that curcumin may increase systemic rosuvastatin exposure by inhibiting hepatic transporters, warranting further investigation into dosing and safety of the combination. Conclusions: While current evidence supports the therapeutic potential of the combined use of rosuvastatin and curcumin, additional pharmacokinetic, mechanistic, and clinical studies are needed to fully assess its translational value.

ABSTRACT Background Climate change poses critical threats to human, animal, and environmental health, yet evidence on integrated One Health responses remains fragmented. Although numerous studies highlight climate‐driven health risks, many climate adaptation frameworks still underrepresent cross‐sectoral interactions and the needs of low‐resource settings. Objective This study aims to identify and operationalize key governance mechanisms, surveillance strategies, and collaborative approaches that can be implemented to support health‐adaptive policies. Methods A comprehensive search of peer‐reviewed literature and international reports (March 2020–June 2025) was conducted across Scopus, PubMed, Web of Science, the World Health Organization (WHO), WHO African region (AFRO), European Centre for Disease Prevention and Control (ECDC), the Food and Agriculture Organization (FAO), and the European Public Health Association (EUPHA) repositories. A narrative synthesis approach was adopted to integrate findings across heterogeneous study designs and contexts. Results Climate change intensifies vector‐borne diseases, heat‐related illness, food insecurity, biodiversity loss, and environmental degradation, disproportionately affecting low‐ and middle‐income countries. Evidence suggests that implementing a One Health approach through effective, evidence‐based actions such as fostering collaborative engagement, using a common operating picture for community‐based surveillance, and strengthening resilient food and livestock production systems that are adaptable to a changing climate could enhance surveillance capacity and accelerate preparedness and early warning processes. Conclusion Significant opportunities exist to improve One Health governance by, among other things, establishing coordinated surveillance systems, flexible policy approaches, an ecosystem‐based perspective, and inter‐sectoral engagement. Currently, policies fail to fully consider environmental and animal health aspects, which could pose significant risks.

Automated license plate readers (ALPRs) are often evaluated as discrete police tools, although their public power arises from cross-vendor socio-technical infrastructure. This article examines roadside and mobile sensors, vehicle-attribute classification, cloud archives, commercial databases, real-time crime center integration, interagency access, automated alerts, and police action. Flock Safety supplies the principal documentary case because unusually extensive public records permit system-level tracing; Axon/Fusus, Motorola Vigilant/VehicleManager, and federal access to commercial ALPR data establish the wider vendor-independent boundary. A structured documentary analysis of 59 sources triangulates official records, peer-reviewed research, vendor materials used only for stated functions, and record-based investigations. It integrates boundary critique, control-structure mapping, feedback analysis, constitutional doctrine, a STRIDE-informed threat model, and empirical research on policing effectiveness and surveillance effects through 3 August 2026. The analysis identifies four conditional mechanisms: infrastructure aggregation, authority diffusion, asymmetric feedback, and rights invisibility. The article reformulates the Rights Control Deficit (RCD) as a non-arithmetic profile relation between operational demands and effective governance capacity and applies it to three documented configurations and a clearly labeled normative benchmark. Seven falsifiable propositions specify variables, indicators, suitable methods, and disconfirming conditions for later empirical study. A rights-preserving hybrid-intelligence architecture combines bounded automation with judicial authorization, short retention, sensitive-location protections, immutable audit, availability safeguards, independent review, contestability, sanctions, and credible termination authority. The evidence identifies capabilities, activated pathways, and conditional risks; it does not estimate population prevalence or a universal ALPR-specific causal effect. Meaningful human oversight is an institutional control property, not merely an officer’s presence at an interface.

Pityogenes chalcographus was monitored using pheromone traps installed in different forest types across Bosnia and Herzegovina. The study was conducted within protected areas of Sarajevo Canton, including the Protected Landscapes of Bijambare and Trebević and the Skakavac Natural Monument. The investigated forest types comprised secondary fir–spruce stands and mixed beech–fir forests with spruce admixture. Data were collected between 2018 and 2021 to assess the effects of forest type and climatic factors on pheromone-trap catches of P. chalcographus. Mean trap catches in secondary fir–spruce forests ranged from 2317.6 to 6317.0 individuals per trap, whereas catches in mixed beech–fir forests with spruce ranged from 150.0 to 6840.0 individuals per trap. The highest mean catches were recorded in the Trebević Protected Landscape and the Skakavac Natural Monument. Overall, trap catches tended to be higher in secondary fir–spruce forests than in mixed beech–fir forests with spruce. Statistically significant differences in mean catches between forest types were detected only in 2021, while no significant differences were observed during 2018–2020. No statistically significant relationships were found between climatic variables and P. chalcographus trap catches during the study period.

BACKGROUND In the C-MIC II trial, C-MIC therapy improved outcomes in patients with heart failure (HF) with reduced ejection fraction (HFrEF). We evaluated whether differences in background HF medication adjustments influenced the observed benefits. METHODS Ambulatory patients with chronic non-ischemic HFrEF receiving guideline-directed medical therapy (GDMT) were enrolled. The primary outcome was change in GDMT and diuretic intensity over 6 months. Treatment effects on left ventricular ejection fraction (LVEF), Kansas City Cardiomyopathy Questionnaire Overall Summary Score (KCCQ-OSS), and 6-minute walk distance (6MWD) were assessed by baseline sodium-glucose cotransporter-2 inhibitor (SGLT2i) use for consistency. RESULTS Among 65 patients, 25 (39%) had GDMT adjustments (C-MIC device: 44%; control 33%; p= 0.390). GDMT intensity increased in controls (Δ +0.36) but decreased (Δ -0.16; p= 0.100) in C-MIC group. Diuretic intensity decreased in C-MIC group (Δ -0.10) but increased in controls (Δ +0.12; p= 0.200). When stratified by baseline SGLT2i use, C-MIC therapy induced consistent improvements in LVEF (SGLT2i: +6% [95% CI 3-9; p<0.001] vs. without SGLT2i: +4% [95% CI 2-7; p=0.003]), KCCQ-OSS (SGLT2i: +42 points [95% CI 26-58; p<0.001] vs. without SGLT2i: +40 [95% CI 28-51; p<0.001]) and 6MWD (SGLT2i: +150 meters [95% CI 88-212; p<0.001] vs. without SGLT2i: +141 meters (95% CI 63-219; p<0.001]). CONCLUSION Medication intensity decreased in C-MIC-treated patients but increased in controls, driven primarily by escalation of diuretics, likely reflecting worsening HF. Consistent improvements in LVEF, 6MWD and KCCQ-OSS across SGLT2i subgroups suggest that the observed benefits are independent of background pharmacologic intensification.

Summary Background WHO's Global Oral Health Action Plan (GOHAP) targets include a 10% relative reduction in the combined prevalence of main oral conditions by 2030. The first GOHAP evaluation was planned for 2023, with subsequent evaluations scheduled for 2026 and 2030. The aim of this systematic analysis of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 was to evaluate global and regional progress (2019–23) towards this target and related complementary indicators. Methods Using modelled estimates from epidemiological surveys and registries in 204 countries and territories, we estimated the age-standardised prevalence of untreated caries in deciduous and permanent teeth, severe periodontitis, edentulism, other oral disorders and orofacial clefts, and the age-standardised incidence of lip and oral cavity cancer. Progress towards GOHAP targets was measured by comparing the percentage change from 2019 to 2023 in the above indicators against the stated GOHAP target of a 10% relative reduction. Findings Globally, the age-standardised prevalence of main oral conditions declined (−1·55% [95% uncertainty interval −2·32 to −0·82]) between 2019 and 2023, but global cases increased by 3·07% (2·32 to 3·75), from 3·62 billion (3·35 to 3·95) to 3·73 billion (3·45 to 4·06). Among complementary indicators, reductions in age-standardised prevalence were observed for untreated caries in permanent teeth (−1·99% [−2·49 to −1·40]) whereas the age-standardised incidence of lip and oral cavity cancer increased (8·35% [0·13 to 16·32]), as did the age-standardised prevalence of orofacial clefts (2·25% [0·77 to 3·83]). Progress was heterogeneous across GBD super-regions, with south Asia having the largest reductions in the age-standardised prevalence of main oral conditions (−3·34% [−4·95 to −1·80]) and untreated caries in deciduous teeth (−9·09% [−17·62 to −0·08]). Sub-Saharan Africa showed the largest increase in prevalent cases of main oral conditions (9·51% [8·09–10·94]) and age-standardised incidence of lip and oral cavity cancer (14·86% [1·19–32·45]). The high-income super-region had an increase in the age-standardised prevalence of main oral conditions (1·24% [0·56–1·96]) and untreated caries in deciduous teeth (9·21% [6·60–11·89]). Interpretation Our modelled estimates of global trends in the prevalence of oral conditions from 2019 to 2023 suggest that early progress is modest and, at the current pace, insufficient to meet the 2030 GOHAP targets. Accelerated, equity-focused prevention and integration of essential oral health-care services within primary care and universal health coverage are needed, alongside strengthened oral cancer control and congenital anomaly care. Funding The Gates Foundation.

This article surveys emerging directions in the mathematics of democracy. It uses three case studies --- voting theory, participatory budgeting, and deliberative democracy --- to highlight how contemporary challenges motivate rigorous mathematical research that incorporates real-world data, institutional constraints, and implementation feasibility. Within each case, we highlight active and promising research frontiers, evidence of real-world impact, practical applications, and opportunities for getting involved.

Blood-based proteomics is approaching a translational inflection point. Driven by advances in measurement technologies, rapid expansion of analytical capabilities, and growing adoption across research and medical communities, there is increasing demand for clinically actionable biomarkers. As the field transitions away from purely large-scale discovery-oriented studies toward more informed, targeted, application-driven analyses, the generation of proteomic data is no longer the bottleneck. Instead, the central challenge is to translate these measurements into robust, reproducible, and clinically meaningful insights. In this Review, we assess recent technological and methodological developments, evaluate persistent preanalytical and interpretative limitations, and outline the key steps required for clinical translation. We focus on three deeply interconnected dimensions: the capabilities and constraints of current measurement platforms, the role of computational and machine learning approaches in extracting biological and clinical signals, and the emergence of large-scale population studies that create new opportunities for validation and generalization. Finally, we discuss a forward-looking vision in which proteomics plays a central role in dynamic, multilayered omics frameworks, where integration with genomics, temporal profiling, and imaging can deepen our understanding of health, disease, and therapeutic response.

Uvod: Dijabetičko je stopalo posljedična komplikacija bolesti dijabetes melitus (DM), odnosno šećerne bolesti. Dijabetes melitus ozbiljna je kronična bolest koja nastaje kad gušterača ne proizvodi dovoljno inzulina za održavanje normalne razine šećera u krvi ili stanice neadekvatno reagiraju na inzulin. Uloga medicinske sestre u zbrinjavanju dijabetičkog stopala ključna je i obuhvaća širok spektar aktivnosti od rane prevencije i edukacije do specifične njege rana. Cilj: Cilj je rada ispitati stupanj znanja i stavova osoba oboljelih od dijabetesa o pravilnoj njezi stopala te procijeniti značaj edukativne i savjetodavne uloge medicinske sestre u prevenciji komplikacija dijabetičkog stopala. Provedeno istraživanje pokazat će koliki je utjecaj zdravstvene njege na ishod liječenja pacijenata s dijabetičkim stopalom i do koje su mjere oboljeli od dijabetesa educirani o pravilnoj njezi stopala. Medicinska je sestra primarni edukator koji pacijenta i njegovu obitelj educira o samopregledu i higijeni. Glavni je cilj spriječiti nastanak ulceracija, inficiranje postojećih rana i izbjeći amputaciju ekstremiteta. Metode: Provedena je prospektivno-deskriptivna studija, a podaci su dobiveni iz ankete koju su pacijenti samostalno popunili te su dali dobrovoljni pristanak za sudjelovanje u istraživanju. Vrsta anekte bila je anketni upitnik, a pitanja vezana za dijabetičko stopalo već su korištena za istraživanje javnozdravstvenog značaja zbrinjavanja dijabetičkog stopala u ordinaciji obiteljske medicine (Završni rad br. 102/SES/2015, Ivana Orban).Za obradu podataka korištene su metode deskriptivne statistike i Student t-test, uz nivo statističke značajnosti p < 0,05. Rezultati: Od ukupnog broja ispitanika u cjelokupnom uzorku, 33 ispitanika navela su da ih diplomirana medicinska sestra savjetuje o tome kako trebaju voditi pravilnu higijenu stopala. U tu skupinu spadaju ispitanici koji su odgovorili da su u posljednjih sedam dana 5 – 7 puta provodili higijenu stopala, što pokazuje da je edukacija pacijenata iznimno korisna. Od ukupnog broja ispitanika u uzorku, čak 32 ispitanika navela su da im najvažniji izvor informacija o njezi stopala predstavlja dipl. medicinska sestra. Zaključak: Na temelju dobivenih rezultata istraživanja i usporedbe s rezultatima drugih istraživanja o istoj temi, možemo zaključiti sljedeće: 1. zdravstvena njega pacijenata oboljelih od dijabetesa uvelike utječe na prevenciju nastanka dijabetičkog stopala; 2. edukacija pacijenata značajno utječe na njihovu svjesnost o mogućim neželjenim komplikacijama koje se mogu spriječiti.

Edible Natural Deep Eutectic Solvents (NADES) offer a route to ready-to-use extracts without solvent removal. This study examined how rational formulation design influences physicochemical properties, extraction performance, energy efficiency, thermal behavior, and cytocompatibility during bioactive recovery from Nigella sativa seeds. Twelve formulations spanning malic acid–polyol, citric acid–polyol, binary polyol, and ternary acid–polyol families were evaluated under standardized ultrasound-assisted conditions and compared with ethanolic ultrasound-assisted extraction, Soxhlet extraction, and cold-pressed oils. Selected NADES formulations outperformed the conventional systems. E1 (malic acid:glycerol:water) achieved the highest total phenolic content and lowest specific energy consumption (40.00 kJ mg−1 GAE), below the Soxhlet benchmark (55.17 kJ mg−1 GAE), whereas E9 (glycerol:xylitol:water) exhibited the greatest ABTS activity. Neat-NADES apparent pH and viscosity were inversely associated with total phenolic content, while viscosity and density were inversely associated with ABTS activity. ATR-FTIR showed stable, solvent-dominated fingerprints over 15 days, whereas DSC better differentiated neat NADES from their extracts. Most systems remained cytocompatible at 10,000× dilution, while acid–polyol formulations reduced viability at 500×; partial neutralization of N5/E5 restored viability. NADES performance was formulation- and application-dependent, requiring joint optimization of composition, acidity, viscosity, energy efficiency, and biologically compatible concentration.

Myelodysplastic syndromes (MDS) are a heterogeneous group of disorders caused by abnormalities at the hematopoietic stem cell level and are associated with ineffective hematopoiesis, peripheral cytopenias, and a propensity for leukemic transformation. Recent research elucidates the key mechanisms and roles of ribosomal proteins (RPs), microRNAs (miRNAs), extracellular vesicles (EVs), and long non-coding RNAs (lncRNAs) in the pathophysiology of MDS. Mutations or altered expression of RP genes lead to ribosomal stress and activation of p53, resulting in impaired erythropoiesis and apoptosis of hematopoietic progenitors. Dysregulation of miRNAs modulates gene expression programs that are essential for hematopoietic differentiation and apoptosis. Moreover, EV-associated miRNAs mediate multiple processes, including intercellular communication and regulation of the bone marrow (BM) microenvironment, thereby contributing to DNA damage and clonal evolution. EV-associated miR-10a and miR-15a have been reported to induce DNA damage in HSCs. LncRNAs have emerged as promising tools for cancer diagnosis and prognostic biomarkers. They play critical roles in regulating malignant cell proliferation, apoptosis, and epigenetic modifications. This overview highlights the molecular complexity of MDS pathogenesis, offering insights to support stratified diagnosis and the development of targeted therapies.

Artificial intelligence (AI) increasingly mediates leadership-relevant judgment through models, dashboards, metrics, decision-support systems, and autonomous agents. This conceptual article develops a socio-technical systems theory of systemically mediated leadership, defined as a nested system-level condition and recurrent process configuration through which human actors, AI systems, organizational routines, governance institutions, and affected stakeholders jointly produce and revise direction, meaning, consequential judgment, legitimacy, and accountability through recursive feedback. A problem-driven conceptual synthesis was updated through 3 August 2026. A structured discovery pass yielded 97 candidate records; 85 sources were retained after relevance screening, citation chaining, concept mapping, and comparison of eight candidate mechanism families. Four proposed qualification conditions jointly define the construct within the present framework: AI mediation, leadership relevance, distributed judgment, and recurrent institutional embedding. Five mechanism families explain transformations in responsibility, legitimacy, control, attention, and feedback timing: moral delegation, interpretive laundering, ceremonial oversight, metric-driven sensemaking, and ethical latency. A causal-loop model specifies justificatory reinforcement, capability atrophy, power insulation, and accountable correction. Their relative dominance produces three ideal-type dynamic regimes: accountable adaptation, stabilized trade-offs, and destructive drift. The theory predicts that organizations using equally accurate models may produce divergent leadership and accountability outcomes because their feedback, power, and oversight architectures differ. Responsible AI leadership thus depends on system architecture and contestable institutional practice, not leader intention, formal human approval, or model accuracy alone.