Abstract: This study analyzes the relationship between digital access and knowledge-economy practices among young Ecuadorian adults, with emphasis on their implications for sustainable digital inclusion and knowledge-based development. The study is based on the premise that access to the Internet, devices, and technological tools does not necessarily ensure critical, productive, collaborative, or knowledge-generating uses of information. A quantitative, non-experimental, cross-sectional, and descriptive-correlational design was applied to a sample of 441 young Ecuadorian adults aged 18 to 30. Data were collected through an online questionnaire and analyzed using descriptive statistics, reliability analysis, KMO and Bartlett indicators, the Mann–Whitney U test, effect sizes, and Spearman’s rho with 95% confidence intervals. The instrument showed very high internal consistency for knowledge-economy practices (α=.978; ω=.978) and digital access and technological resources (α=.963; ω=.964). The KMO values were also adequate for both variables (.963 and .902, respectively), and Bartlett’s tests were statistically significant (p<.001). The results showed that digital access received more favorable ratings than knowledge-economy practices. A very strong, positive, and statistically significant association was found between digital access and knowledge economy practices (ρ=.822, 95% CI [.765, .870], p<.001). Information management and collaboration was the dimension most strongly associated with digital access (ρ=.820, 95% CI [.764, .868], p<.001). Women reported higher scores than men in knowledge-economy practices, although the effect size was small (r=.158; rrb=.184). These findings suggest that digital access is a necessary but insufficient condition for sustainable digital inclusion. The study contributes empirical evidence from a developing-country context and highlights the need for educational and public-policy strategies that transform connectivity into critical learning, collaboration, innovation, and knowledge creation.

Abstract: This prospective case series evaluated the short-term outcomes following percutaneous cementoplasty as the sole palliative treatment for appendicular osteosarcoma in 10 dogs. Synthetic self-hardening calcium-phosphate bone substitute was injected into the osseous defect under fluoroscopic guidance after curettage of the bone tumor. Clinician assessment included a numerical rating score for lameness, offloading, and ease of lifting the contra-lateral limb as well as the 4A-VET post-operative pain scale. Owner assessment was obtained using three descriptive questionnaires, the Helsinki Chronic Pain Index (HCPI), the Canine Brief Pain Inventory (CBPI) and the Canine Symptom Assessment Scale (CSAS). Measures were recorded preoperatively and at 2-, 4-, 8-, and 12-weeks following surgery. Early improvement in the 4A-Vet score was noted at the 2-, 4-, 8-, and 12-week time points for all major pain and function metrics. Similarly, the CBPI pain severity and interference scores demonstrated early postoperative improvement during the 2- and 4-week time points with partial attenuation by 8- and 12-weeks. Panting, difficulty sleeping, whining/moaning, and lack of appetite were significantly reduced when assessed via the CSAS. Cementoplasty as a monotherapy, affording early pain relief and improved structural integrity, supports its role as a limb-sparing option for dogs unable to undergo amputation.

Abstract: The accelerating accumulation of atmospheric carbon dioxide (CO₂) from fossil fuel combustion represents one of the foremost environmental challenges of the twenty-first century. This paper presents the design, theoretical basis, and experimental framework of a novel artificial photosynthesis system capable of capturing CO₂ from combustion flue gases and converting it into oxygen (O₂) and energy-rich compounds, directly mimicking the biochemical process performed by trees. The proposed system integrates a sodium carbonate (Na₂CO₃) absorption tower for CO₂ capture, a thermal desorption unit for solvent regeneration, and a cobalt oxide-catalyzed photosynthetic reactor for CO₂-to-O₂ conversion. System performance is quantified using non-dispersive infrared (NDIR) sensors for CO₂ measurement and electrochemical oxygen sensors for O₂ detection. Stoichiometric analysis indicates that 1 kg of captured CO₂ yields approximately 0.73 kg of O₂, and national-scale deployment projections suggest energy savings of approximately $200 billion per year by 2030 alongside a potential reduction of 302,600 million metric tons of CO₂ emissions. Comparative analysis with existing decarbonization approaches—including carbon capture and storage (CCS), hydrogen production, and enhanced oil recovery (EOR)—demonstrates that artificial photosynthesis offers a fundamentally superior outcome by permanently transforming CO₂ into life-sustaining O₂ rather than merely sequestering or displacing it. This work establishes a laboratory-scale proof of concept and a systematic experimental roadmap for scaling the technology to industrial application.

Abstract: The growing demand for high-efficiency, high-power-density converters in data centers, electric vehicle chargers, and renewable energy systems has accelerated the adoption of wide bandgap (WBG) devices. Gallium nitride (GaN) transistors offer superior switching speed, lower losses, and higher power density compared with Silicon (Si) devices. Accurate characterization of GaN switching dynamics is essential due to parasitic effects and transient phenomena affecting performance and reliability. The Double Pulse Test (DPT) is widely used to quantify critical parameters, including switching energy losses, dynamic RDS(on) and transient voltage and current waveforms. This paper reviews DPT techniques for GaN devices, focusing on measurement methodologies, parasitic mitigation, and reliability considerations, providing practical guidance for optimizing high-frequency GaN-based power converters.

Abstract: Expanding renewable energy capacity in sub-Saharan transmission systems is a cornerstone of sustainable development, yet weak grid infrastructure and the absence of flexible storage remain principal barriers to reliable and low-carbon energy access. This paper addresses the economic and environmental dimensions of that challenge by proposing a hierarchical multi-objective framework for the optimal siting and sizing of Battery Energy Storage Systems (BESS), applied to the 130-bus Mali transmission network within the EMERGE project. The upper level employs the NSGA-II evolutionary algorithm to simultaneously maximize daily price-arbitrage revenue—the economic sustainability indicator—and minimize active power losses—the environmental efficiency indicator. For each candidate design, the lower level solves a multi-period DC Optimal Power Flow (DC-OPF) via CasADi/IPOPT, with thermal branch constraints embedded as hard linear inequalities through the Power Transfer Distribution Factor (PTDF) matrix, and voltage-corrected loss estimates recovered via a vectorized Extended DC Power Flow (EDCPF) model. Over 500 NSGA-II generations, the framework identifies Bus 91 (SIRAKORO II, 150 kV) as the dominant storage location, achieving maximum daily revenue of approximately € 10,033 at a marginal loss increment of 6.7×10⁻³ MWh. The Pareto front provides Mali system planners with a quantitative tool for balancing private investment returns against grid-level environmental impact, demonstrating that rigorous network-constrained BESS planning is both technically tractable and economically viable in the resource-constrained context of sub-Saharan sustainable energy transitions.

Abstract: This study evaluates the feasibility of using asphalt concrete as an impermeable core material for rockfill dams under tropical conditions. Laboratory testing and numerical modeling were conducted to assess the hydraulic and mechanical performance of asphalt concrete mixtures produced with locally available aggregates in Thailand. Asphalt mixtures were designed using the Marshall method with asphalt binder contents of 6% and 7% and target air void contents between 1-4%. Laboratory testing included permeability testing, Marshall stability testing, and triaxial compression tests to determine hydraulic conductivity, shear strength parameters, and deformation characteristics. Results show that asphalt concrete mixtures with air void contents below 1% exhibit extremely low permeability, with hydraulic conductivity on the order of 10⁻¹¹–10⁻¹² m/s, satisfying requirements for impervious dam cores. Triaxial compression tests yielded cohesion values between 97-572 kPa and friction angles ranging from 31° to 52°, indicating adequate shear resistance. Numerical simulations performed using GeoStudio compared rockfill dams with asphalt concrete cores and conventional clay cores. The results demonstrate that a 0.5‑m‑thick asphalt concrete core provides comparable seepage control and slope stability while requiring significantly smaller material volume. The findings suggest that asphalt concrete cores represent a technically feasible and economically advantageous alternative to clay cores, particularly in regions where suitable clay materials are limited.

Abstract: Walking is not merely locomotion but a window into the nervous system, integrating cortical, subcortical, cerebellar, spinal, and peripheral networks into a unified motor behavior. Across neurological diseases—including Parkinson’s disease, atypical parkinsonism, cerebellar ataxias, stroke, multiple sclerosis, neuropathies, neuromuscular disorders, and functional gait syndromes—gait disturbances are among the most disabling clinical features, contributing to falls, loss of independence, institutionalization, and premature mortality. Traditional bedside observation remains indispensable, but it lacks the sensitivity and reproducibility needed to capture subtle, episodic, or prodromal abnormalities. Over the past decade, advances in wearable sensors, marker-based and markerless motion capture, pressure-sensitive walkways, force plates, artificial intelligence, and machine learning have positioned digital mobility outcomes as promising, ecologically valid biomarkers of neurological function. These measures can support differential diagnosis, provide prognostic information on falls and survival, and serve as sensitive endpoints in therapeutic trials. They may also detect early abnormalities, such as increased stride-to-stride variability or prolonged double-support time, before overt clinical deterioration becomes evident. Clinical applications are increasingly evident across disorders, including distinguishing Parkinson’s disease from atypical parkinsonism, quantifying treatment response in normal-pressure hydrocephalus, tracking progression in ataxia and multiple sclerosis, predicting functional decline in motor neuron disease, and guiding rehabilitation after stroke. Integration with neuroimaging, electrophysiology, and molecular biomarkers is beginning to reveal the circuits underlying variability, instability, and freezing, positioning gait as a systems-level marker of neural integrity. Nevertheless, methodological heterogeneity, limited disease-specific validation, insufficient longitudinal data, and lack of consensus on clinically meaningful parameters continue to constrain translation. Cognitive, affective, and environmental influences also remain insufficiently represented in digital frameworks, while equity, accessibility, algorithmic bias, and privacy require careful ethical governance. Reconceptualizing gait as a “sixth vital sign” reframes mobility as a multidimensional biomarker of neural and systemic health. With harmonized protocols, robust validation, multimodal integration, and appropriate ethical frameworks, gait analysis could become a cornerstone of precision neurology.

Abstract: Moisture content is a critical parameter influencing the durability, structural performance, and maintenance of timber structures. However, current building inspection practices often rely on subjective interpretation, resulting in inconsistent assessment outcomes and ineffective maintenance decision-making. Despite the availability of various moisture measurement techniques, a standardized framework for interpreting moisture levels in relation to timber condition is still lacking. This study presents a structured review and synthesis of moisture content thresholds reported in the literature and proposes a standardized classification framework for timber defect assessment. The findings indicate that moisture content levels can be systematically categorized into four condition states dry, moderate, poor, and critical for each associated with specific maintenance actions. The proposed framework provides a practical linkage between moisture measurements and condition-based maintenance strategies, enabling more consistent and reliable inspection practices. The study contributes by transforming dispersed moisture-related data into a unified and actionable classification system, serving as a decision-support tool for building inspectors and maintenance practitioners. The proposed framework enhances the implementation of condition-based maintenance by reducing subjectivity and improving the accuracy of timber condition assessment.

Abstract: Rainfall and groundwater fluctuations may influence the migration or dilution of contaminants from US Superfund sites. This pilot study was designed to provide empirical data on relationships between rainfall and contaminant concentrations in water near Superfund sites. Four Superfund sites on Long Island, New York were selected to represent a range of contaminant profiles and hydrogeologic conditions. Baseline samples were collected in December 2022, with subsequent samples obtained following major storms and seasonally through September 2023. Samples were collected on 11–24 different days across the sites and measured for metals and 1,4-dioxane. Overall, we observed few consistent associations between rainfall and contaminant concentrations across sites. Two trends, however, were noted: (1) At Gowanus Canal, a surface water site, there was a negative association between rainfall and contaminant concentrations using same-day or prior-day rainfall; and (2) in a treatment well near Lawrence Aviation, negative associations were observed between prior month’s rainfall and contaminant concentrations. Rainfall appeared to dilute contaminant concentrations at two of the four Superfund sites. Given the increased frequency and intensity of extreme rainfall events, it is important to continue probing links between rainfall and contaminants near Superfund sites.

Abstract: Agentic artificial intelligence systems increasingly combine language models, memory, retrieval, tool use, orchestration, and human oversight. For software engineering, this creates a variability problem that feature-oriented product line methods only partly address: organizations are configuring not only functions or components, but permitted patterns of agency. Unlike MAS-SPL, which mainly structures families of agent roles and interactions, the proposed approach targets LLM-based agents whose prompts, retrieval sources, tool authority, runtime monitoring, and governance boundaries vary together. This paper proposes Agency-Centric Product Line Engineering for governed agentic AI systems. It defines agency variability as systematic variation in a system's capacity to pursue goals, perceive context, reason and plan, use tools, exercise authority, interact with humans or other agents, remain observable, and evolve under governance constraints. It also defines semantic observability as runtime monitoring of whether semantic behavior—goals, tool choices, evidence use, proposed actions, and escalation decisions—remains consistent with the granted agency profile. The paper contributes a nine-dimension Agency Variability Model, an Agency Configuration Schema, a constraint-based validation algorithm, and a prototype-style derivation of portfolio-management agent variants. The case shows that five variants can share assets while differing in perception, authority, autonomy, human control, and topology.

Abstract: The hexane extract of Psoralea drupacea Bunge fruits was initially evaluated for antivi-ral activity against SARS-CoV-2 based on GC-MS data indicating high bakuchiol con-tent (87.74%). Unexpectedly, the extract showed no antiviral effect in Vero E6 cells due to cytotoxicity (CC₅₀ = 7.5 μg/mL), while purified bakuchiol demonstrated moderate antiviral activity (IC₅₀ = 6.2 ± 0.8 μg/mL; SI = 2.9). Quantitative NMR revealed that the actual bakuchiol content in the extract was 44.3% — approximately half the GC-MS value — explaining the lack of efficacy at non-cytotoxic concentrations. Both the ex-tract and purified bakuchiol effectively blocked the RBD-ACE2 interaction in a com-petitive ELISA (71.3% inhibition at 50 μM for bakuchiol; IC₅₀ = 18.5 μM). Notably, the extract also inhibited the viral main protease 3CLpro (IC₅₀ = 32.0 ± 3.5 μg/mL), while purified bakuchiol showed no such activity. These findings reveal a dual mechanism: bakuchiol inhibits viral entry via RBD-ACE2 blockade, while other extract components (e.g., angelicin, psoralen) suppress viral replication via 3CLpro inhibition.

Abstract: Background and Objective: Treat-and-extend(TREX) dosing is widely used for anti-VEGF therapy in macular disease but no principled basis exists for choosing interval-change rules. We frame TREX as a threshold-search problem and compare rules in terms of search efficiency and overshoot.Patients and Methods: A deterministic model represented TREX as a threshold search for the true maximum dry interval(T_max) on a 1-week grid(4–16 weeks). Four rules were evaluated:+2/−2,+4/−2,+4/−4 with midpoint refinement, and a midpoint binary-like rule. Visits to maintenance interval and overshoot metrics were calculated for each rule and T_max.Results: No single rule was optimal. The +2/−2 rule minimised overshoot (maximum 2 weeks) but required most visits. The +4/−2 rule was fastest. In long-durability eyes, midpoint search matched +4/−2 in speed with overshoot comparable to +2/−2.Conclusion: Framing TREX as a threshold search makes the speed-overshoot trade-off explicit and provides a principled basis for choosing and justifying interval-change rules.

Abstract: Standard cryptocurrency transaction cost models assume flat geometry and assign execution cost as a proportional fee. This paper tests whether replacing flat-fee models with a unified Riemannian execution cost framework improves out-of-sample prediction of realised execution costs. The framework identifies execution slippage as the geodesic arc length on the Fisher information manifold of a Markov-switching GARCH maximum-entropy model, augmented by a joint curvature-topological fragmentation alarm derived from the same parameter vector. Ablation confirms that each geometric component contributes uniquely: removing the geodesic increases mean squared prediction error by 2.9%, removing topological data analysis by 2.1%, and removing curvature by 1.5%. No subset matches the full framework. On five major cryptocurrency markets (BTC, ETH, XRP, LTC, BCH) over 2,253 daily observations, the integrated framework achieves the lowest prediction error on all five assets and is the sole model retained in the Model Confidence Set at the 10% significance level against six benchmarks, including Amihud, Kyle λ, and Almgren and Chriss. A joint curvature-topological alarm fires a median of two days before price-based circuit breaker thresholds across four crisis episodes, including the Terra collapse of May 2022 and the FTX bankruptcy of November 2022. The framework requires no additional data or free parameters beyond the upstream estimation pipeline.

Abstract: Diabetic peripheral neuropathy (DPN) remains a leading cause of disability in diabetes, yet current care is largely symptomatic. Increasing evidence places early dysfunction of the blood-nerve barrier (BNB)—a core element of the peripheral nerve neurovascular unit (PNVU)—at the intersection of metabolic stress and neuroinflammation. This review synthesizes a redox-centered model of BNB failure in DPN: (i) chronic hyperglycemia and dyslipidemia overwhelm endogenous antioxidant defenses, driving reactive oxygen species (ROS) imbalance; (ii) ROS-associated endothelial activation promotes endothelial-immune crosstalk, leukocyte recruitment, and macrophage polarization; and (iii) progressive loss of tight-junction and barrier homeostasis increases paracellular permeability and exposure of nerves to pro-inflammatory and neurotoxic mediators. We then evaluate incretin-based therapies—GLP-1 receptor agonists, DPP-4 inhibitors, and emerging multi-agonists—as potential modulators of PNVU/BNB stress. Beyond glucose and weight effects, these agents may dampen oxidative and inflammatory signaling, engage antioxidant pathways (e.g., Nrf2), and potentially support molecular determinants of BNB integrity via indirect metabolic unloading and possible GLP-1R-dependent vascular-immune actions. By reframing DPN as a neurovascular-immune disorder driven by redox imbalance, we highlight barrier-focused biomarkers and hypothesis-generating therapeutic opportunities that require clinical validation.

Abstract: The Warburg effect is a metabolic phenomenon observed in cancer cells and is characterized by aerobic glycolysis instead of mitochondrial oxidative phosphorylation as the primary mechanism of cellular energy generation. The exact benefit of such a metabolic switch is poorly understood, as aerobic glycolysis is thermodynamically more inefficient than mitochondrial oxidative phosphorylation. Here, we present a case of a 40-year-old male with advanced stage 4 hepatocellular carcinoma with chronically low glucose levels measured in the 20s to 40s and completely asymptomatic. Upon examination, findings of sympathetic hyperactivity in the setting of hypoglycemia were absent, and mentation was completely intact. This occurred in the absence of any states or medications known to induce hypoglycemia; concurrently, the patient demonstrated hyperphagia, suggesting increased metabolic demand in the setting of an immense, overwhelming tumor burden. During these hypoglycemic intervals, the patient's coagulation profile, including PT and international normalized ratio, remained within normal limits, suggesting sufficient residual hepatic parenchyma and glucogenic capacity. The patient's glucose remained extremely low, refractory to correction with multiple dextrose, D5, and D10 administrations. This suggests chronic systemic habituation to malignant cell consumption of serum glucose leading to adaptations to this hypoglycemia in highly metabolically active organs, such as the brain, heart, liver, and kidneys. This report highlights the clinical utility of recognizing this metabolic state in the setting of advanced-stage malignancy with significant tumor burden and how it affects hospital glucose management. Its early recognition will lead to improvements in meeting the patient's metabolic demands while avoiding paradoxical exacerbation of lactic acidosis when providing guideline-directed oncological treatment. This metabolic state may function as a surrogate marker, in conjunction with serum markers and imaging studies, for clinical identification of advanced stage malignancies and for treatment escalation.

Abstract: Background/Objectives: Artificial intelligence (AI) has emerged as a promising tool to improve the detection and characterization of small bowel (SB) lesions through endoscopic imaging. This scoping review aimed to map and synthesize the available evidence regarding the diagnostic performance of AI systems applied to capsule endoscopy (CE) and device-assisted enteroscopy for the identification of SB lesions with potential malignant or premalignant relevance. Methods: A scoping review was conducted following the frameworks of Arksey and O’Malley, Levac, and Joanna Briggs Institute recommendations, and reported according to PRISMA-ScR guidelines. Searches were performed in PubMed, Scopus, and Embase. Original studies evaluating AI systems on SB endoscopic images or videos and reporting quantitative diagnostic metrics were included. Data extraction covered study characteristics, imaging modality, AI task, diagnostic performance, and methodological limitations. Results: A total of 13 studies were included, with a predominance of retrospective designs (9/13; 69.2%), followed by one prospective study (1/13; 7.7%), and one pilot study (1/13; 7.7%). Most studies originated from China (4/13; 30.8%, including an international collaboration with Denmark) and Japan (4/13; 30.8%). CE was the predominant imaging modality (9/13; 69.2%), followed by device-assisted enteroscopy (2/13; 15.4%) and upper gastrointestinal endoscopy (1/13; 7.7%). Automated lesion detection was the main application of artificial intelligence, reported in most studies (11/12; 91.7%), frequently combined with diagnostic classification tasks (8/12; 66.7%). Most models were based on convolutional neural networks, including architectures such as ResNet50 (29), Single Shot Multibox Detector (28), YOLOv5 (30), and nnU-Net (32). Diagnostic performance was consistently high, with sensitivities ranging from 81.2% to 98.6%, specificities from 88.6% to 99.8%, and area under the ROC curve values approaching 1.0 in several studies (22–30,33). Conclusion: AI improves the detection of SB lesions and significantly reduces endoscopic reading times, particularly in CE. Nevertheless, current evidence remains insufficient to support the use of AI as a screening tool for SB cancer, mainly due to the predominance of retrospective studies and the lack of robust prospective multicenter validation.

Abstract: Background: Assessing the quality of ICU care directly from the patient’s perspective is challenging. Therefore, it is essential to train health professionals with resources that allow them to evaluate family satisfaction, with reliable and valid instruments, capable of supporting staff, managers and family members in the management of care centered on the person and family. The Family Satisfaction with Care in the Intensive Care Unit 24 (FS-ICU 24) is the most reliable and valid measure of family satisfaction. Recently the FS-ICU was revised and little psychometric evaluation has been done on the FS-ICU 24R. Objective: This study aimed to evaluate the psychometric properties of FS-ICU 24R using the version, translated and adapted to Brazilian Portuguese. Methods: The data was collected with 200 family members of patients admitted to Intensive Care Units in three hospitals in the state of Rio Grande do Sul between October 2021 and January 2022. The coefficient α-Cronbach was used to determine the internal consistency of FS-ICU 24R. The validity of the revised questionnaire and its subscales was performed by factorial (construct), discriminant, and convergent validity. The construct was tested by exploratory factor analysis with Varimax orthogonal rotation. The relationship between observed variables and latent variables was evaluated through Confirmatory Factor Analysis, with testing of models suggested in exploratory factor analysis and by the main author of the questionnaire, through adequacy indexes and comparison of the models. Results: The evaluation of internal consistency showed a α-Cronbach of 0.97. The results of the exploratory factor analysis showed that the number of items was preserved; however, instead of the two factors present in the original questionnaire, three were retained, explaining 74.20% of the data variance, with a Kaiser-Meyer-Olkin indicator of 0.95 and eigenvalue of 1.10. In the Confirmatory Factor Analysis, the three factors presented factorial loadings above 0.70; the values of the Average Variance extracted were above 0.5, and composite validity indexes above 0.70. The instrument maintained the same items but distributed in three factors (the first factor “overall satisfaction”, includes satisfaction with the atmosphere, communication, and support of professionals to the family; the second factor ‘family satisfaction with patient care’, and the third ‘satisfaction with the decision-making process'). Conclusions: We conclude that the FS-ICU 24R questionnaire was valid and reliable to evaluate the satisfaction of families in Intensive Care Units but that the use of sub-scale scores may be dependent on context or version of the questionnaire.

Abstract: Background: Current international hereditary angioedema (HAE) guidelines and treat-to-target recommendations consistently emphasize accurate diagnosis, early on-demand treatment of attacks, appropriate short-term prophylaxis for procedures, individualized long-term prophylaxis (LTP), and routine assessment of disease control and quality of life. Published information on how these recommendations are implemented in Latin America remains limited. We therefore aimed to assess the extent to which a Latin American expert panel converges with recommendations across current international HAE guidelines and consensus documents and to identify the principal barriers affecting real-world implementation in the region. Methods: A scientific committee developed and externally validated a 74-item questionnaire (domains summarized in Supplementary Table S1) and conducted a 2-round Delphi process among Latin American HAE experts. Consensus items were rated on a 9-point agreement scale, with consensus defined a priori as at least two-thirds of panelists scoring within a 3-point band in the agreement (7-9) or disagreement (1-3) range. Descriptive items captured expert-reported diagnostic testing, acute and preventive treatment patterns, monitoring practices, and implementation determinants using 5-point Likert scales. Instrument validation (July-November 2024) demonstrated high inter-rater agreement (Kendall W = 0.84; p < 0.001) and excellent internal consistency (Cronbach alpha = 0.92). Results: Thirty experts from 10 countries completed the process (Argentina, Brazil, Chile, Colombia, Ecuador, Mexico, Panama, Peru, Uruguay, Venezuela). Panel consensus broadly converged with recommendations across current international HAE guidelines and consensus documents on core diagnostic work-up (C4 plus C1-INH antigen and function; 84% consensus), selective use of genetics (97% consensus), first-line targeted LTP (pdC1-INH, Lanadelumab, Berotralstat; 94% consensus), retention of on-demand therapy for breakthrough attacks and for patients without access to LTP, routine monitoring, and management in special populations. The principal novel finding was an implementation feasibility gap: frequent or constant interruptions in prophylaxis supply were reported by 19/30 experts (63%), including 13/23 (57%) practicing in settings where public or insurance coverage was reported. Across the panel, cost (19/30; 63%) and medicine availability (8/30; 27%) were the most commonly cited barriers, with additional constraints related to diagnostic testing access and administrative pathways. Conclusions: Latin American expert consensus largely converges with recommendations across current international HAE guidelines and consensus documents on diagnosis, acute management, prophylaxis selection, monitoring, and special-population care. The dominant divergence is not clinical disagreement but implementation feasibility—particularly access to diagnostic testing, financing mechanisms, medicine availability, and continuity of supply. These findings provide region-specific evidence to contextualize international recommendations and support implementation strategies tailored to Latin America.

Abstract: Background and Objectives: Myocardial injury after noncardiac surgery (MINS) is a major determinant of perioperative morbidity and mortality. Its largely silent clinical course often makes early diagnosis difficult and challenging. Cardiac Cycle Efficiency (CCE), is a new parameter that reflects the energy efficiency of the cardiovascular system. This study aimed to evaluate the relationship between intraoperative CCE values and postoperative myocardial injury. Materials and Methods: This prospective observational study included 50 adult patients. The CCE parameters, including baseline CCE, minimum CCE, mean CCE, ΔCCE, and the duration and percentage of CCE<0, were continuously recorded. In all patients, high-sensitivity troponin I (hs-TnI) levels were measured on the postoperative days 1, 2, and 3. The primary endpoint was defined as exceeding the 99th percentile upper limit of the hs-TnI values. Results: Postoperative troponin elevation above the 99th percentile upper reference limit was identified in 11 patients (22%); none of these patients had accompanying ischemic symptoms or new ECG changes. Comparison of CCE-derived parameters between the elevated and normal troponin groups yielded no statistically significant differences for any variable (MinCCE p=0.87, MeanCCE p=0.74, DeltaCCE p=0.69, CCE index p=0.50, time with CCE<0 p=0.19, CCE<0 percentage p=0.51). Spearman rank correlation analysis similarly demonstrated no significant association between any CCE parameter and peak troponin levels; the closest trend was observed for MinCCE (r=–0.244, p=0.08), which nonetheless did not reach statistical significance. On ROC curve analysis, none of the CCE parameters exhibited meaningful discriminative ability, with the highest AUC recorded for cumulative time with CCE below zero (AUC=0.63, 95% CI: 0.43–0.83, p=0.19). Conclusions: Intraoperative CCE parameters failed to predict postoperative troponin elevation in patients at low-to-moderate risk undergoing elective noncardiac surgery. These findings indicate that CCE is not a reliable, standalone predictive marker in this patient population. Studies involving higher-risk patient groups and larger sample sizes are required.

Abstract: Rising complexity in cyber-physical systems development exposes challenges in the consistent and reusable specification of graphical domain-specific languages (DSLs). Despite the benefits of model-based systems engineering (MBSE), the absence of a standardized, lifecycle-wide specification process results in semantic inconsistencies, tool dependence, and limited interoperability. While our previous work has addressed individual stages of DSL definition, a comprehensive, standards-based process integrating these stages remains missing. Building on these foundations, this paper introduces a unified language specification process for graphical DSLs grounded in established standards---the Meta-Object Facility (MOF), Unified Modeling Language (UML), Web Ontology Language (OWL), and Resource Description Framework (RDF). The process integrates three core artifacts: a tool-independent ontology capturing domain semantics, a MOF-conformant metamodel unifying abstract syntax, semantics, and concrete syntax, and a UML-profile-based implementation. To support and exemplify this process, a prototypical toolchain is introduced that enables automated transformations between these artifacts, thereby facilitating the consistent propagation of semantics from ontology to implementation. The applicability of the proposed process is demonstrated through both a top-down automotive case and a bottom-up cybersecurity DSL, illustrating its cross-domain generalizability. By explicitly structuring and connecting ontology, metamodel, and implementation, this work contributes a semantically consistent, machine-interpretable, and tool-independent specification process for graphical DSLs in MBSE.