Abstract: Selection bias in Large Language Models has emerged as a fundamental obstacle to reliability, fairness, and robustness. Defined operationally as systematic decision changes under equivalence-preserving input perturbations, including option permutation, label renaming, candidate-order swapping, and evidence relocation, the phenomenon is examined across four representative task families: multiple-choice question answering, in-context classification, LLM-as-a-Judge evaluation, and long-context or retrieval-augmented generation. Selection bias is first analyzed through a causal chain that links biased behavior to training-data priors, architectural asymmetries, and post-training amplification. Existing mitigation methods are then synthesized through an intervention-level taxonomy spanning inference-time calibration and prompt optimization, architecture-level modification, and training-level debiasing. The evaluation landscape is unified by summarizing commonly used metrics, benchmark families, and application settings, with the lack of standardized and cross-task-comparable protocols identified as a central bottleneck. Selection bias is best understood as a failure of invariance under non-semantic reformatting, and mitigating it is essential for trustworthy, robust, and selection-invariant language models.

Abstract: The paper introduces a fundamental shift in the representation of physical reality, moving from a particle-based paradigm to a Recursive Complex Representation of 5 scaling levels (RCR) of a “hypophenomenal” geometric model. A unique scaling base ξ is defined that is deduced from the Planck constant and the gravitational constant G. The model posits that space is not a static container but a Plenum (David Bohm’s name for vacuum) of Planck contiguous cells (P-cells) whose vibrations constitute the fundamental energy of the universe. Masses are “trapped light”, viewed as localized vibrational resonances of the signal c that maintain a portion of the signal within contiguous groups of P-cells, and can propagate along the plenum by keeping their internal vibrational configuration. The fine-structure constant α acts within a universal renormalizing factor, strictly related to the scaling factor ξ = (GL_P)^1/5. Experimental masses, across 60 orders of magnitude (from the neutrino to the Sun) are retrieved from their ξ logarithmic localization with respect to Planck’s mass. The fundamental equations of Planck, Einstein, and de Broglie are not independent postulates, but natural geometric emergences of the signal’s vibrational dynamics. Gravitational force and constant G are formulated in terms of matter aggregation and dynamic curvature of the signal in the Plenum.

Abstract: Background/Objectives: Obstructive sleep apnea (OSA) is a common and serious sleep-related disorder that causes repeated interruptions in breathing during sleep. Traditional diagnostic methods, such as polysomnography, are accurate but costly, time-consuming, and unsuitable for large-scale screening. This study proposes and evaluates a lightweight diagnostic framework based on an Extreme Learning Machine (ELM) optimized by a set of basic and advanced metaheuristic optimizers (GA, RUN, MEO, CL-PSO, HI-WOA, GWO, HGS, HHO, SeaHO, MGO, and the hybrid GWO--WOA). The model aims to improve early detection of OSA using demographic and clinical data. Methods: Two real datasets were employed to train and evaluate the proposed framework: (i) a clinical OSA dataset with 274 subjects and 31 demographic/anthropometric and sleep-related predictors, and (ii) a public strongly imbalanced Sleep-Disordered Breathing (SDB) dataset with 500 subjects and 10 structured predictors. Metaheuristic algorithms are used to optimize ELM weights and biases, addressing the instability of random initialization and improving model generalization. The optimized models are evaluated against eight baseline classifiers, including Logistic Regression (LR), k-nearest neighbours (KNN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Multilayer Perceptron (MLP), XGBoost (XGB), and a standard ELM classifier. Results: Results show that metaheuristic optimization improves ELM on the OSA dataset, increasing ROC-AUC from 0.6527 to about 0.73 and accuracy from 0.6573 to about 0.69–0.70, while on the highly imbalanced SDB dataset, it yields modest ROC-AUC gains (from 0.5132 to about 0.544–0.548) with small decreases in accuracy and F1-score. Conclusions: The proposed framework provides a fast, lightweight, and cost-effective screening tool for large-scale, resource-limited healthcare settings, enabling early OSA detection and preventive intervention.

Abstract: Implant-supported overdentures improve denture retention and patient satisfaction, but debonding of attachment housings from the denture base remains a frequent prosthetic complication. This in vitro study evaluated the influence of attachment housing and denture base materials on debonding occurrence and maximum tensile force in resin-cemented attachment housing–denture base complexes subjected to cyclic mechanical loading. Thirty standardized specimens were digitally designed and fabricated from 3 denture base materials—polymethylmethacrylate (PMMA), polyetheretherketone (PEEK), and cobalt-chromium (Co-Cr)—and combined with either titanium or PEEK attachment housings, which were bonded with a dual-polymerized resin cement. Specimens were subjected to 1,100 cycles of alternating tensile and compressive loading, and debonding occurrence and maximum tensile force were recorded. Debonding occurred in 60% of specimens and differed significantly among denture base materials, with no debonding observed in Co-Cr specimens, whereas debonding occurred in 75% of PMMA and PEEK specimens. Co-Cr specimens also demonstrated significantly higher maximum tensile force values than PMMA and PEEK groups, while attachment housing material showed no significant effect. Within the limitations of this in vitro study, the denture base material significantly influenced debonding and tensile force during cyclic loading, whereas the attachment housing material did not demonstrate a significant main effect.

Abstract: Heme-containing enzymes play vital functions in living organisms, including humans. Here we demonstrate two indirect effects of (electric discharge)-treated stainless steel on a model enzyme — horseradish peroxidase (HRP). The first effect is the complete loss of the enzyme’s adsorption after its incubation in grounded stainless steel chamber, which has been preliminarily subjected to electric discharge in air at atmospheric pressure. The second one is the formation of enzyme aggregates in the sample incubated in another grounded chamber two meters away from the discharge-treated one. At that, the HRP’s enzymatic activity is found to be unaffected in the both cases. These effects may be explained by the occurrence of knotted electromagnetic fields (KEMF). By using high-speed atomic force microscopy (HS-AFM), we reveal the relatively high surface mobility of cytochromes P450cam and P450 102A1 (BM3), whose isoelectric point (pI) values are acidic; at that, thymidylate synthase (TYMS) with near-neutral pI adsorbs strongly. Thus, HRP is the best model object, since its basic pI provides quite strong adsorption on mica. Since (electric discharge)-processed materials have found applications in medicine, we expect that the effects discovered will be considered in future biomedical applications of (electric discharge)-based technologies.

Abstract: This paper, which is entirely unconditional, proves a sharpened almost-all theorem with fully explicit effective constants for the restricted weighted Goldbach sum R_{a,q}(N) := sum over p1+p2=N, p1 = a (mod q), of (log p1)(log p2), with q >= 1 and gcd(a,q) = 1, whose expected main term is M_{a,q}(N) = C_2 * S(N) * N / phi(q), where C_2 = 0.6601618... is the twin-prime constant and S(N) is the binary singular series.The results are organised around four pillars.(I) A complete character-pair decomposition of the second moment of the error E(N) := R_{a,q}(N) - M_{a,q}(N), extracting the exact diagonal constant G/(2*phi(q)), where G = prod_{p>2}(1 + (p-1)^{-2}) in [1.41320886, 1.41320899] is the Gallagher-Goldston constant.(II) A uniform minor-arc L^4 bound: integral over minor arcs of |S(alpha)|^4 dalpha <= kappa_safe * 2^A * X^3 / (log X)^A, with kappa_safe = 4.40, obtained by combining the complete Vaughan identity with the Bombieri-Vinogradov theorem in integral form, with an explicit derivation of kappa_explicit = C_V^2 * c_{L^2} = 4.004 before applying a rigorous 10% safety margin.(III) The effective almost-all theorem: #{N <= X even : |R_{a,q}(N) - M_{a,q}(N)| > C(A,q) * N * (log N)^{-3}} << X * (log X)^{-A}, with the explicit constant K := 2*C(1,4) <= 3.3624, obtained from C(1,4) <= 1.6812 via a Stechkin-type optimisation.(IV) A Pintz-type exceptional-set bound on {N <= X : R_{a,q}(N) = 0}.Every statement in the main body carries the tag [PROVED]. No Generalised Riemann Hypothesis, no zero-density hypothesis, no ternary sum W_{a,q}(n), no spectral input, and no Chen-type sieve are used anywhere.

Abstract: Heat stress severely constrains wheat productivity, yet the mechanisms underlying thermotolerance remain incompletely understood. In this study, we integrated physiological, biochemical, molecular, and ultrastructural analyses to characterize heat-stress responses in four bread wheat (Triticum aestivum L.) genotypes contrasting in heat tolerance. Membrane thermotolerance was assessed using electrolyte leakage and membrane damage rate under increasing temperature stress, while antioxidant defense was evaluated by measuring the activities of superoxide dismutase, catalase, guaiacol peroxidase, and benzidine peroxidase. Gene expression responses were analyzed by qRT-PCR for DREB, HSP16.9, and compartment-specific SOD isoforms, while HSP16.9 accumulation was validated at the protein level by Western blotting. Heat stress induced progressive membrane destabilization in all genotypes. However, the tolerant genotypes Murov 2 and Zirva 85 maintained greater membrane stability than the sensitive genotypes Aran and Gyzyl bugda. This physiological advantage was accompanied by stronger activation of antioxidant defenses, enhanced induction of DREB and HSP16.9, and a more coordinated expression pattern of FeSOD and MnSOD, indicating integrated redox regulation across chloroplastic and mitochondrial compartments. HSP16.9 protein was undetectable under control conditions but accumulated after heat treatment, confirming its stress-inducible nature and supporting its role in heat-responsive proteostasis. Correlation analysis revealed a coordinated response module linking DREB, HSP16.9, MnSOD, total SOD, BPX, CAT, and GPX. Microscopy further showed that Murov 2 preserved chloroplast, mitochondrial, and mesophyll organization more effectively than Aran under heat stress. Collectively, these findings demonstrate that wheat thermotolerance is governed by the coordinated protection of membranes, redox homeostasis, molecular chaperone systems, and organelle structure, providing potential physiological and molecular targets for breeding heat-resilient wheat cultivars.

Abstract: Toxoplasmosis is a prevalent zoonotic disease worldwide, affecting approximately one-third of the global human population. Primary infection with Toxoplasma gondii during pregnancy can induce miscarriage or congenital infection, leading to irreversible damage to the foetus. Moreover, reactivation of T. gondii infection in immunosuppressed individuals can result in fatal outcomes. No vaccine exists to prevent human disease caused by this parasite. Thus, a vaccine that could induce complete and lasting protection against human toxoplasmosis is an unmet need. In this work, a subunit vaccine, consisting of T. gondii membrane proteins (TGMP) from the T. gondii Me49 strain plus CpG-oligodeoxynucleotide adjuvant (CpG), was tested using BALB/cByJ mice. Intranasal immunisation with TGMP plus CpG (TGMP+CpG) raised TGMP-specific serum IgG and intestinal IgA antibody levels, and parasite-specific IFN-γ-producing CD4+ and CD8+ memory T cells. Dense granule proteins (GRA) 2 and 7, surface antigen (SAG)-related sequences 25, 29B, and 34A, microneme protein (MIC) 10, toxofilin, nascent polypeptide-associated complex (NAC) domain-containing protein and NAC subunit beta were identified as immunogenic proteins in the TGMP. Mice immunised with TGMP+CpG were challenged with T. gondii tachyzoites and showed a significant reduction in the parasitic burden in the peritoneal exudate, spleen, and lungs, compared to mice sham-immunised with CpG alone. Altogether, these results indicate that mucosal immunisation with TGMP plus CpG adjuvant is worth exploring as a vaccination approach to prevent toxoplasmosis.

Abstract: Streptococcus pyogenes and Streptococcus agalactiae are major Gram-positive patho-gens implicated in recurrent and invasive genital infections, and the rise of antimicrobial resistance underscores the need for alternative localized therapies. This study combined molecular docking with a prospective pilot clinical evaluation of an essential-oil-based vaginal capsule formulation intended for localized intravaginal administration. Terpinen-4-ol, isoflavone, and secoisolariciresinol diglucoside (SDG) were analyzed against two bacterial targets - the redox-sensing transcriptional repressor Rex from S. agalactiae and the protein tyrosine phosphatase from S. pyogenes - using the 1-Click Docking platform and the Lamarckian Genetic Algorithm. In parallel, 47 women aged 19-27 years were identified with vaginal and/or cervical colonization or infection caused by S. agalactiae or S. pyogenes, and 34 of them entered a prospective pilot treatment study with once-daily vaginal capsules for 7 days; persistent positive cases received an additional 7-day course. Isoflavone and SDG showed the most favorable interactions against the S. agalactiae target, while SDG also displayed comparatively favorable interaction against the S. pyogenes target. In the clinical pilot cohort, microbiological eradication after completion of therapy reached 91.7% for S. agalactiae and 80.0% for S. pyogenes. The parallel trend between stronger in silico prioritization for the S. agalactiae-directed target and higher clinical eradication in the pilot cohort supports a cautious translational hypothesis, but the absence of a control group, the limited sample size, and the exploratory nature of the clinical dataset require restrained interpretation. Overall, these findings support further controlled studies designed to test whether the computationally prioritized phytocompounds contribute to measurable in vivo benefit within localized antimicrobial strategies.

Abstract: This article investigates how an e‑learning platform and a virtual reality (VR) workshop simulator can be integrated into a traditional craft apprenticeship without displacing workshop‑based learning. Drawing on the Craeft glassblowing Pilot 1 at CERFAV, it reports a two‑phase mixed‑methods study contrasting a Traditional Augmented (TA) group, which used a Craeft e‑learning platform and a VR glassblowing simulator, with a Traditional (T) control group following the standard Certificate of Professional Competence (CPC) programme. Quantitative data from formative assessments and CPC examination results are combined with qualitative feedback, satisfaction surveys, self‑assessment questionnaires, and interviews with apprentices and trainers. In Phase 1, where digital tools were deployed in a separated mode alongside existing instruction, the e‑learning platform was perceived as pedagogically valuable, but effects on assessment outcomes were limited and uneven, with greater score dispersion in the TA group. In Phase 2, redesigned hybrid usage scenarios assigned distinct and complementary roles to the e‑learning platform, VR, and workshop practice within an iterative learning cycle, yielding more consistent advantages for the TA group in cross‑cutting theoretical subjects and reducing variance in their scores. Qualitative analyses show that apprentices adopt a pragmatic stance towards digital tools, using the e‑learning platform primarily for revision and exam preparation and VR for workshop discovery and tool recognition, while maintaining a strong attachment to material practice. The study concludes that, in small, high‑stakes craft VET programmes, the impact of virtual learning environments depends less on their intrinsic properties than on their orchestration within coherent hybrid designs and on trainers’ capacity to align them with authentic tasks and assessment regimes.

Abstract: Climate change is intensifying droughts, heatwaves, and hydrological extremes, increasing crop vulnerability and threatening global food security. This study analyzes the scientific evolution of research on remote sensing-based crop climate vulnerability, with emphasis on temporal, geographical, and thematic patterns. A quantitative, exploratory, descriptive, longitudinal, and retrospective bibliometric approach was applied to 2,343 documents indexed in Scopus between 1985 and 2026. The dataset was processed using Bibliometrix 5.1.1 and VOSviewer 1.6.20 to evaluate productivity, impact, collaboration, and intellectual structure, including Reference Publication Year Spectroscopy (RPYS). Results show a sustained annual growth rate of 4%, with 627 sources, 10,408 authors, an average of 5.17 co-authors per document, 35.3% international collaboration, and 19.93 citations per document. China, the United States, and India lead scientific production, while key journals concentrate dissemination. Thematic analysis highlights the dominance of drought-related studies and the increasing importance of machine learning and cloud-based platforms such as Google Earth Engine. The findings indicate that the field has reached a stage of scientific and technological maturity, transitioning from descriptive monitoring toward predictive and operational geospatial intelligence. However, challenges remain in methodological integration, geographical representation, and the translation of scientific outputs into decision-oriented tools for agricultural adaptation.

Abstract: Purpose: This study examined the acute effects of High-Intensity Interval Training (HIIT) and prolonged endurance training (ET) on heart rate variability (HRV) in elite Greco-Roman wrestlers. A secondary aim was to assess the usefulness of HRV in opti-mizing recovery strategies by monitoring post-exercise changes. Methods: Using a longitudinal crossover design, 13 elite male wrestlers completed two training protocols separated by a 15-day washout period. HRV variables were recorded at baseline, pre-exercise, during training, and 24 hours post-exercise. Data were analyzed with a linear mixed model (LMM) and Bonferroni-adjusted post hoc comparisons. Results: A significant main effect of Timepoint was found for all HRV parameters (SDNN, RMSSD, LF/HF ratio, and overall HRV), indicating marked reductions during exercise fol-lowed by partial recovery after 24 hours. A significant effect of Training Type was ob-served for SDNN. Post hoc analysis showed a significantly greater suppression of overall HRV during HIIT compared to ET (p = .012, Cohen’s d = 0.82). Despite these differences, both protocols demonstrated similar recovery patterns at 24 hours. Conclusion: Both HIIT and ET induced acute decreases in HRV, with HIIT causing a more pronounced decline. Nevertheless, HRV recovery after 24 hours was comparable between the two training modalities.

Abstract: This work deals with the time-domain analysis of asymmetrical faults in three-phase systems. Conventional three-phase analysis provides steady-state solutions for asymmetrical faults. Transient analysis, however, is usually performed by resorting either to oversimplified approximate circuits, or to numerical methods. In this paper, a rigorous analytical methodology based on the time-domain Clarke transformation is presented for the most common asymmetrical faults in three-phase systems. In particular, it is shown that asymmetrical faults result in circuit coupling in the Clarke equivalent circuits. Circuit representation of coupling is also derived in the paper. Coupled equivalent circuits allow rigorous analytical solution of transients in case of asymmetrical faults. The analytical results derived in the paper are validated through proper numerical simulation of faulted radial systems.

Abstract: Methylated flavonoids are abundant phytochemicals in Eucalyptus and are of interest be-cause methylation can alter flavonoid diversity, bioactivity and stability. The enzymes re-sponsible for flavonoid methylation in eucalypts are largely uncharacterised. We used comparative leaf transcriptomics of two species with contrasting flavanone profiles, together with protein-structure-guided candidate selection, to identify prospective O-methyltransferases (OMTs) involved in methylated flavonoid biosynthesis. Five candidate OMTs from E. eugenioides were cloned, heterologously expressed and assayed against a panel of flavonoids and a chalcone precursor. The enzymes showed distinct substrate preferences and regioselectivities. EeOMT1 acted as a broad 7-O-methyltransferase, whereas EeOMT3–EeOMT5 preferentially methylated B and C-ring hydroxyl groups, with differing capacities for sequential methylations at different sites. EeOMT2 was of particu-lar interest because it effectively methylated pinocembrin chalcone to alpinetin chalcone, while only weakly converting pinocembrin to alpinetin. Expression–metabolite analyses across E. eugenioides genotypes supported roles relating to in planta accumulation of 5-O- and 7-O-methylated flavanones, for EeOMT2 and EeOMT1, respectively. These findings support a revised model in which alpinetin biosynthesis proceeds, at least in part, through methylation of a chalcone precursor before flavanone formation. This provides a foundation for elucidating flavonoid methylation pathways and for engineering tailored methylated flavonoids for industrial applications.

Abstract: The aim of the study was to analyse the epidemiological characteristics of confirmed COVID-19 cases in the Tumbes region between March 2020 and December 2022. Method: An ecological design with a descriptive approach was used for the study population, which consisted of 51,421 confirmed cases of COVID-19 registered as confirmed cases of COVID-19 residing in the provinces of Contralmirante Villar, Tumbes, and Zarumilla in the department of Tumbes. Confirmed cases of COVID-19 reported in SISOVID by the Ministry of Health and the registry of confirmed cases of COVID-19 in all age groups were recorded. The sociodemographic data collected was supplemented with information available on the web platform of the National Institute of Statistics and Informatics (INEI). The data were organised into databases, georeferenced and analysed using software such as RStudio, applying epidemiological indicators (incidence, prevalence, mortality and lethality). The spatial and epidemiological data were organised and analysed in a database prepared in Microsoft Excel, in order to consolidate the information through data filtering and organisation. Results: Among the main findings, a decrease in incidence was observed between 2021 (7,840/100,000 inhabitants) and 2022 (5,721/100,000 inhabitants), although prevalence increased from 15% to 20%. The mortality rate fell significantly from 2.57 per 1,000 inhabitants in 2021 to 0.33 in 2022. The highest fatality rates were concentrated among people over 60 years of age with comorbidities, especially men. Conclusion: The pandemic was unevenly distributed, affecting adults between 30 and 59 years of age, populations with pre- existing conditions, and densely populated urban areas the most. Spatial analysis made it possible to identify critical areas for improving the health response. It is recommended to strengthen epidemiological surveillance, improve access to health services in densely populated areas, and prioritise care for vulnerable groups such as older adults and indigenous peoples.

Abstract: The Automobile industry shifts from linear to circular economy for sustainability on a global level with respect to the industrial revolution 5.0, but it faces challenges when establishing circular economy. Circular supply chain implementation is dependent on multiple barriers and enablers, including economic managerial, technological, regulatory and social domains, making it ineffective for single factor solution. The purpose behind this review is to conduct a systematic literature review to develop an understanding how these interconnected barriers and enablers can together shape the circular supply chain implementation and their performance, specifically inside the automotive sector which is still remain a little known. By applying the PRISMA framework on 150 peer reviewed articles, research papers. The research shows that literature focuses on primarily on electric vehicle barriers within developing economies. circular supply chain implementation is governed not only by isolated barriers but by complex systematic interdependencies between enablers as well. This interdependencies are of enablers and barriers can be further classified into economical and financial, managerial and organizational, technological and infrastructure, policy and regularity and market and social. The study shows two systematic patterns, driving the transition technology- policy interdependence and conflicting relationship between large scale production and value extraction. The findings also presented a research agenda focusing on strategic value creation through material streams of automotive electronics, plastics and composites with high potential value and further insights are needed. Circular supply chain as a strategic approach for securing critical material supplies, while policymakers could leverage the use of digital tools as the foundational infrastructure for subsidies allocation and prevent the fraud.

Abstract: Background/Objectives: Acute exercise can influence executive function, but the neurophysiological responses linking exercise to cognitive change remain unclear. Functional near-infrared spectroscopy (fNIRS) provides a feasible method for assessing prefrontal oxygenation during movement-based exercise. This study examined whether prefrontal oxygenated hemoglobin (oxy-Hb) during exercise was associated with subsequent changes in inhibitory control after aerobic and game-based exercise in young adults.Methods: Twenty-four healthy young adults completed aerobic and game-based exercise conditions in a randomized, counterbalanced, within-subject design. The aerobic condition consisted of jogging, whereas the game-based condition consisted of a pickleball-based activity. Exercise intensity was monitored during both conditions. Prefrontal oxy-Hb was recorded during exercise using fNIRS, and inhibitory control was assessed before and after each condition using an Eriksen Flanker task. The primary behavioral outcome was Flanker cost improvement, and the primary fNIRS outcome was mean baseline-corrected prefrontal oxy-Hb during exercise. Results: Exercise intensity was comparable between conditions. Greater mean prefrontal oxy-Hb during exercise was significantly associated with greater improvement in Flanker cost (β = 3.71 ms per 0.01 μM, 95% CI [2.13, 5.30], p < 0.001). Game-based exercise elicited higher mean prefrontal oxy-Hb during exercise than aerobic exercise. No significant condition difference was observed for Flanker cost improvement. Conclusions: Prefrontal oxygenation during exercise was associated with subsequent improvement in inhibitory control. These findings suggest that neurophysiological responses during exercise may account for some between-person variability in acute exercise-related cognitive benefits.

Abstract: Soft robotics is a rapidly evolving field that has attracted significant attention within the scientific community. This review analyzes the main advantages of pneumatic technology in service robots across the different application domains defined by the International Federation of Robotics (IFR). By organizing the literature according to application domains, this work aims to clarify the specific benefits of pneumatic and soft pneumatic solutions in each context. The proposed approach distinguishes between traditional pneumatic solutions and the subsequent emergence of soft robotics, in order to highlight how and to what extent soft technologies have reshaped the design and application scenarios. Particular attention is devoted to the role of materials and recent manufacturing techniques used by researchers to fabricate soft pneumatic robots. Finally, current research trends are discussed, with the goal of identifying key directions for the further development of soft pneumatic service robots.

Abstract: Background: Non-communicable diseases (NCDs) account for the majority of global mortality, yet healthcare systems remain largely oriented toward the treatment of acute conditions. This study examines the structural mismatch between contemporary disease patterns and healthcare system organization. Methods: A narrative analytical review was conducted using secondary data from the Global Burden of Disease (GBD) study and World Health Organization (WHO) reports, supplemented by literature from PubMed, Scopus, and Google Scholar (2000–2026). Findings were interpreted using epidemiological transition theory, health systems analysis, and political economy frameworks. Results: The analysis identifies multiple structural drivers of treatment-oriented healthcare systems, including economic incentives favoring curative services, short-term political decision-making cycles, and the historical dominance of the biomedical model. These factors contribute to systematic underinvestment in prevention, rising healthcare expenditures, and persistent global inequalities in access to medical technologies, as demonstrated during the COVID-19 pandemic. The current model is associated with increasing economic burden and projected losses in global productivity by 2030–2050. Conclusions: The findings indicate that the current healthcare model is structurally misaligned with population health needs. Improving health outcomes and system sustainability requires a reorientation toward prevention, long-term health metrics, and the evidence-based integration of complementary approaches within healthcare systems.

Abstract: Background: Although Diagnostic Reference Levels (DRLs) based on anatomical regions are widely used in Computed Tomography (CT) imaging, a clinical-indication-based approach provides a more accurate representation of daily practice and protocol variation. This study aimed to establish typical radiation doses for common CT clinical indications among adult patients at King Abdulaziz University Hospital (KAUH) in Saudi Arabia. Methods: This retrospective cross-sectional study included 298 adult patients who underwent CT examinations between 2020 and 2025 using two dual-source scanners operating in single- and dual-source modes. Demographic data, acquisition parameters, and radiation dose metrics, including volume CT dose index (CTDIvol) and the dose–length product (DLP) were extracted from scanner consoles. Six clinical indications were analyzed: brain trauma, sinusitis, chest metastases (chest Mets), interstitial lung disease (ILD), abdominopelvic metastases (AbdPel Mets), and hernia. Results: Typical median CTDIvol values in mGy were 36.4 for brain trauma, 3.4 for sinusitis, 4.9 for chest Mets, 5.6 for ILD, 7.2 for AbdPel Mets and hernia. Corresponding DLP values in mGy·cm were 654, 50, 173, 188, 344, and 369, respectively. Brain trauma demonstrated the highest radiation exposure, whereas sinusitis CT showed the lowest. Most values were comparable to or lower than international DRLs. Conclusions: This study provides the first comprehensive clinical-indication-based DRL data in Saudi Arabia beyond anatomical benchmarks, supporting ongoing dose optimization and future national DRL development.