Search Results (52,494)

This study examines the determinants of inflation volatility in Tunisia, focusing on central bank independence (CBI), economic transparency, and macroeconomic fundamentals. Although CBI is widely regarded as essential for monetary credibility, its effectiveness depends on its institutional framework. Our contribution is twofold. First, we develop a theoretical framework based on game theory to illustrate how the effectiveness of economic transparency and CBI shapes the welfare of both the central bank and the private sector in the presence (or not) of fiscal policy. Second, we use a binary threshold nonlinear autoregressive distributed lag (NARDL) model to capture long-run relationships and a Markov-switching GARCH (MS-GARCH) framework to model volatility dynamics. As a continuous measure, CBI has no significant impact on volatility. Paradoxically, high de jure independence in a binary regime is associated with a slight increase in inflation fluctuations. This indicates that legal independence alone is insufficient without fiscal discipline or effective coordination between the monetary and fiscal authorities. Notably, under fiscal pressure, greater CBI substantially reduces inflation volatility, highlighting the need for a coherent macroeconomic framework. Economic transparency generally increases short-term volatility but stabilizes inflation when supported by credible fiscal signals. Among the macroeconomic fundamentals, volatility in broad money is strongly destabilizing, whereas fluctuations in industrial production and the real exchange rate are largely insignificant. Government spending and exposure to external shocks, including import prices and geopolitical risks, further amplify this volatility. The observed negative trend over time reflects gradual improvements owing to policy reforms. Policy recommendations emphasize the establishment of genuinely independent and credible monetary institutions, enhancing coordination with fiscal policy, improving communication strategies, and strengthening risk management. Full article

Background: KMT2A rearrangements are a frequent genetic abnormality associated with Acute myeloid leukemia (AML), historically linked to varied prognoses and outcomes. The prognosis for patients with this rearrangement remains controversial, necessitating further research to stratify risk and guide treatment. Methods: In this retrospective study, a total of 3468 adolescent and adult AML patients were screened, and 181 patients harboring KMT2A rearrangements were analyzed. We used FISH, RT-PCR, and next-generation sequencing, including transcriptome and targeted panels, for diagnosis and mutation profiling. All patients received intensive chemotherapy. We evaluated overall survival and event-free survival using Kaplan–Meier and Cox regression models, with HSCT analyzed as a time-dependent variable. Results: The incidence of KMT2A-rearranged AML in our newly diagnosed cohort was 5.9%. Among the 181 patients included in the final analysis, 89 (49.2%) were male and 92 (50.8%) were female, with a median age of 33 years (range: 13–65). The distribution of fusion partners included KMT2A::MLLT3 (n = 39), KMT2A::AFDN (n = 27), KMT2A::MLLT10 (n = 25), KMT2A::ELL (n = 24), and others (n = 12). Seventy-four patients underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) in first complete remission (CR1). The median follow-up for survivors was 17.53 months (range 1.47–112.57), and the 3-year overall survival (OS) and event-free survival (EFS) for the entire cohort were 42.0% and 32.1%, respectively. Patients with KMT2A::ELL exhibited superior OS compared to other subtypes (3-year OS [ELL vs. non-ELL]: 59.8% vs. 39.3%, p = 0.023). Concomitant mutations did not significantly impact the prognosis of KMT2A-rearranged AML patients. In multivariate analysis, age and HSCT in CR1 were independently associated with OS and EFS (OS: HR = 1.022, p = 0.026 [age]; HR = 0.238, p < 0.001 [HSCT]; EFS: HR = 1.027, p = 0.002 [age]; HR = 0.155, p < 0.001 [HSCT]). Patients aged over 20 years were more likely to benefit from HSCT than those aged 20 years or younger (p < 0.001 [age > 20], p = 0.780 [age ≤ 20]). Conclusions: Our study revealed the heterogeneous outcomes of KMT2A-rearranged AML patients and clarified the impact of HSCT across different age groups. Full article

Thermal control represents one of the most important parameters influencing the safety and reliability of lithium-ion batteries, especially at high rates required for modern electric vehicles. The present paper investigates the thermal and electrothermal performance of a lithium iron phosphate (LiFePO₄) battery pack using a combination of experimental, statistical, and numerical methods. The 8S5P module was assembled and examined under load tests of 200, 400, and 600 W with and without active air-based cooling. The findings indicate that cooling reduced cell surface temperature by up to 10 °C and extended discharge time by 7–16% under various load conditions, emphasizing the effect of thermal management on battery performance and safety. In order to more systematically investigate the impact of ambient temperature and load, a RSM study with a central composite design (CCD; 13 runs) was performed, resulting in two very significant quadratic models (R² > 0.98) for peak temperature and discharge duration prediction. The optimum conditions are estimated at a 200 W load and an ambient temperature of 20 °C. Based on experimentally determined parameters, a finite-element simulation model was established, and its predictions agreed well with the measured results, which verified the analysis. Integrating measurements, statistical modeling, and simulation provides a tri-phase methodology to date for determining and optimizing battery performance under the electrothermal dynamics of varied environments. Full article

Background: Attention Deficit Hyperactivity Disorder (ADHD) is associated with executive function deficits—such as planning, organization, and prospective memory—that impair autonomy and daily functioning, increase family stress, and create challenges in educational contexts. These consequences underscore the need for accessible and ecologically valid interventions addressing the cognitive, familial, and educational dimensions. Traditional approaches often lack ecological validity, and pharmacological treatment shows a limited impact on functional cognition. Objectives: This protocol outlines a feasibility study of DiverAcción, a web-based telerehabilitation system designed to enhance functional cognition through interactive and gamified tasks integrated into a comprehensive healthcare programme. Methods: A quasi-experimental feasibility study before and after the study will recruit 30 participants aged 9 to 17 years with ADHD. The study comprises an initial face-to-face session for instructions and baseline assessment (T0), followed by twelve supervised online sessions over six weeks. Therapeutic support is provided via integrated chat, email, and two scheduled videoconference check-ins. Feasibility outcomes: include recruitment, adherence, retention, usability (SUS), acceptability (TAM), satisfaction, user-friendly design, therapeutic alliance (WAI-I), and professionals’ attitudes toward technology (e-TAP-T). Exploratory measures: include parental self-efficacy (BPSES), parenting stress (PSI-4-SF), ADHD symptomatology (SNAP-IV), executive functioning (BRIEF-2), time management (Time-S), emotional regulation (ERQ-CA), prospective memory (PRMQ-C), and health-related quality of life (KIDSCREEN-52). Analyses emphasize descriptive statistics for feasibility metrics (recruitment, adherence, retention, dropout and fidelity). Assessments are conducted post-intervention (T1) and at three-month follow-up (T2) and analyzed relative to baseline using repeated-measures ANOVA or Friedman tests, depending on data distribution. Conclusions: This feasibility protocol will provide preliminary evidence on the usability, acceptability, and implementation of DiverAcción. Findings will guide refinements and inform the design of a subsequent randomized controlled trial. Full article

This paper concentrates on fractional-order fuzzy cellular neural networks (FOFCNNs) with bounded uncertainties and transmission delays. To better capture real-world dynamic behaviors, the fuzzy AND and OR operators are employed to construct drive-response systems. For the fixed-time synchronization task of the systems, a novel multi-module feedback controller incorporating three functional terms is designed. These terms aim to eliminate delay effects, ensure fixed-time convergence, and reduce parameter conservativeness. Leveraging the properties of fractional-order operators and our multi-module control scheme, new synchronization criteria of the studied drive-response systems can be established within a predefined time. An upper bound on the settling time is derived, depending on the system size and control parameters, but independent of the initial conditions. A significant corollary is derived for the case of no uncertainties under the nonlinear controller. Numerical experiments discuss the impact of uncertainties and delays on synchronization, and confirm the validity of the results presented in this study. Full article

We present a unified description of dense matter and neutron star structure based on simple but physically motivated models. Starting from the thermodynamics of degenerate Fermi gases, we construct an equation of state for cold, catalyzed matter by combining relativistic fermion statistics with the liquid drop model of nuclear binding. The internal stratification of matter in the outer crust is described by the $\beta$-equilibrium, neutron drip and a gradual transition to supranuclear matter. Short-range repulsive interactions inspired by Quantum Hadrodynamics are incorporated at high densities in order to ensure stability and causality. The resulting equation of state is used as input in the Tolman–Oppenheimer–Volkoff equations, yielding self-consistent neutron star models. We compute macroscopic stellar properties including the mass–radius relation, compactness and surface redshift that can be compared with recent observational data. Despite the simplicity of the underlying microphysics, the model produces neutron star masses and radii compatible with current observational constraints from X-ray timing and gravitational-wave measurements. This work demonstrates that physically transparent models can capture the essential features of neutron star structure and provide valuable insight into the connection between dense-matter physics and astrophysical observables; they can also be used as easy-to-handle models to test the impact of more complicated phenomena and variations in neutron stars. Full article

High-precision temperature prediction is crucial for dealing with extreme weather events under the background of global warming. However, due to the limitations of computing resources, numerical weather prediction models are difficult to directly provide high spatio-temporal resolution data that meets the specific application requirements of a certain region. This problem is particularly prominent in areas with complex terrain. The use of remote sensing data, especially high-resolution terrain data, provides key information for understanding and simulating the interaction between land and atmosphere in complex terrain, making the integration of remote sensing and NWP outputs to achieve high-precision meteorological element downscaling a core challenge. Aiming at the challenge of temperature scaling in complex terrain areas of Southwest China, this paper proposes a novel deep learning model—Terrain Adaptive U-Net Transformer (TAUT). This model takes the encoder–decoder structure of U-Net as the skeleton, deeply integrates the global attention mechanism of Swin Transformer and the local spatiotemporal feature extraction ability of three-dimensional convolution, and innovatively introduces the multi-branch terrain adaptive module (MBTA). The adaptive integration of terrain remote sensing data with various meteorological data, such as temperature fields and wind fields, has been achieved. Eventually, in the complex terrain area of Southwest China, a spatio-temporal high-resolution downscaling of 2 m temperature was realized (from 0.1° in space to 0.01°, and from 3 h intervals to 1 h intervals in time). The experimental results show that within the 48 h downscaling window period, the TAUT model outperforms the comparison models such as bilinear interpolation, SRCNN, U-Net, and EDVR in all evaluation metrics (MAE, RMSE, COR, ACC, PSNR, SSIM). The systematic ablation experiment verified the independent contributions and synergistic effects of the Swin Transformer module, the 3D convolution module, and the MBTA module in improving the performance of each model. In addition, the regional terrain verification shows that this model demonstrates good adaptability and stability under different terrain types (mountains, plateaus, basins). Especially in cases of high-temperature extreme weather, it can more precisely restore the temperature distribution details and spatial textures affected by the terrain, verifying the significant impact of terrain remote sensing data on the accuracy of temperature downscaling. The core contribution of this study lies in the successful construction of a hybrid architecture that can jointly leverage the local feature extraction advantages of CNN and the global context modeling capabilities of Transformer, and effectively integrate key terrain remote sensing data through dedicated modules. The TAUT model offers an effective deep learning solution for precise temperature prediction in complex terrain areas and also provides a referential framework for the integration of remote sensing data and numerical model data in deep learning models. Full article

People living with and beyond cancer often face ongoing challenges related to nutrition, wellbeing, and long-term health. Many individuals express a need for evidence-based, tailored dietary support, yet practical approaches to sustaining healthy eating behaviours remain limited. Culinary nutrition interventions, which integrate nutrition education with hands-on culinary skills, may help address these needs; however, their effects have not been systematically synthesised. This systematic review evaluates the impact of culinary nutrition interventions, delivered alone or in combination with physical activity or mental health components, on dietary intake, psychosocial and health-related outcomes, anthropometric measures, clinical and metabolic markers, and feasibility among individuals living with or beyond cancer. Following PRISMA guidelines, 18 studies were identified across PubMed, Scopus, EMBASE, CINAHL, and Web of Science (last searched in April 2025) and narratively synthesised. A total of 1173 participants were included, with sample sizes ranging from 4 to 190 participants per intervention. Interventions were well received and rated as highly acceptable, with strong engagement and minimal adverse effects. Across studies, statistically significant improvements were reported in dietary intake (7/13 studies), quality of life (4/5), mental health (5/6), self-efficacy (2/3), symptom management (3/4), self-reported cognitive health (1/1), food-related behaviours (2/2), selected anthropometric measures (4/8), and selected metabolic biomarkers (4/6). The evidence suggests that culinary nutrition interventions hold promise as supportive, behaviour-focused strategies aligned with oncology nutrition guidelines and responsive to patient needs. However, due to heterogeneity across interventions and outcomes, and variability in methodological quality as assessed using the Cochrane risk of bias tool, quantification of effects was not possible, limiting interpretation of the evidence. Further high-quality studies using comparable outcome measures and longer-term follow-up are needed to quantify the magnitude of effects, assess their durability over time, and inform the integration of culinary nutrition programmes into cancer care. This systematic review is registered under the PROSPERO ID CRD42024567041 and was funded by the RCSI Research Summer School Fund. Full article

As structural engineers face increasing pressure to minimize the embodied carbon of building components, selecting appropriate materials is critical for sustainable design. Thiemission ts study evaluates the life cycle performance of engineered bamboo beams to determine their viability as a low-carbon alternative to traditional timber in structural framing applications. Utilizing OpenLCA software and the Ecoinvent database, a cradle-to-grave analysis was conducted to inform material selection for the Australian construction context. A parametric design study compared two specific bamboo species, Moso and Asper, against traditional Laminated Veneer Lumber (LVL) to identify the optimal material for minimizing environmental impact. The assessment revealed that Asper bamboo beams represent a superior design choice; a 30.74 kg strand-woven functional unit (FU) achieved net-negative emissions of −13.30 kg CO₂e under 2025 conditions. This offers a significant design advantage over traditional LVL options, which are net-positive emitters, and outperforms Moso bamboo, which yielded higher net emissions (+24.60 kg CO₂e) due to lower sequestration rates. Furthermore, dynamic analysis demonstrated the temporal efficiency of this material in the structural life cycle: in the time required for a single Radiata Pine rotation, Asper bamboo completes five growth cycles, storing a net 103.25 kg of CO₂e per functional unit. Confirmed by a sensitivity analysis for robustness, these findings provide quantitative design criteria supporting the integration of Asper bamboo into sustainable building standards and structural specifications. Full article

Imaging moving targets in synthetic aperture radar (SAR) remains a significant challenge due to the defocusing and azimuthal displacement caused by target motion. To address this, this paper proposes a velocity estimation and motion compensation technique to mitigate the impact of moving targets on SAR imaging quality. The core innovation of this study lies in a wake-independent method for determining the radar beam center crossing time. Unlike traditional approaches that rely on wake features, our proposed method determines the crossing time by detecting the abrupt change in echo intensity along the time axis (i.e., the azimuth direction) of the time–frequency spectrum. Using this estimated timing, the target’s radial and azimuthal velocities are estimated. Subsequently, using the estimated velocity, the motion compensation of the moving target echoes is carried out through phase correction. Due to the difficulty in obtaining AIS data strictly synchronized with real SAR acquisitions, simulation data are initially utilized to verify the proposed method. The simulation results of moving ships with different velocities under three incidence angles demonstrate that the estimated errors of the radar radial and the azimuthal velocities generally remain below 0.1 m/s (2% relative error) and 0.5 m/s (5% relative error), respectively. Furthermore, after motion compensation, the azimuthal displacement caused by radial velocity is effectively corrected, restoring targets to their actual positions. Finally, the Level-0 raw data of ships acquired by Sentinel-1 SAR are applied to further verify the effectiveness of the method proposed in this paper. Full article

Background/Objectives: With the global rise in chronic diseases among older adults, rehabilitation services have become essential, particularly for those with cerebrovascular and central nervous system (CNS) disorders, which lead to significant long-term disabilities. To determine the impact of designated rehabilitation medical institutions on the readmission rates of older patients with CNS disorders who receive surgical interventions. Methods: This was a population-based cohort study. Data was obtained from the National Health Insurance Service database (2002–2019). Fifteen designated institutions participated in the pilot project for convalescent rehabilitation. We analyzed the data of 1019 patients before and after the implementation of the designated rehabilitation institution. The study sample included (1) patients admitted to 15 designated institutions participating in the pilot project for convalescent rehabilitation and (2) patients diagnosed with conditions classified under the rehabilitation patient group, Rehabilitation Impairment Category 1 to 7. The intervention was the pilot project for designated rehabilitation institutions, launched in October 2017. The primary outcome of interest was the readmission rate of older patients with CNS disorders who received surgical interventions. Interrupted time series analysis with segmented regression was used to assess changes in the 30-day readmission rates. Results: Post-intervention, an 8% reduction in 30-day readmission rates (estimate, 0.9225; 95% confidence interval: 0.9129–0.9322, p < 0.0001) was observed. Subgroup analysis showed a significant decline in readmission rates across various patient groups, including those with disabilities, high Charlson Comorbidity Index scores, and extended hospital stays. The regions outside Seoul (capital city), particularly Gyeonggi/Incheon (areas around Seoul) and other areas (i.e., rural), also showed a significant decrease in readmission trends after the intervention. Conclusions: Designated rehabilitation medical institutions led to a significant reduction in readmission rates of older patients with CNS disorders, suggesting that these institutions effectively support recovery and reduce the burden of readmission for patients with severe conditions and those residing in non-capital cities. Full article

This study evaluated the effect of time of botulinum toxin A (BoNT-A) treatment on clinical outcomes in adults with post-stroke spasticity (PSS). Individual data were pooled from five studies. Eligible patients received ≥1 BoNT-A injection(s) for PSS and had goal attainment scaling (GAS) scores measured at baseline and 12 weeks. Patients were grouped according to time of treatment post-stroke: early (<1 year) or late (≥1 year). The primary endpoint was the total GAS (GAS-T) score change from baseline to 12 weeks. Secondary outcomes included the proportion of patients with a GAS-T score ≥ 50. Overall, 968 patients were included (166 early and 802 late). Median time post-stroke to BoNT-A treatment was 0.5 (early) versus 5.4 (late) years. Mean (standard deviation [SD]) baseline GAS scores were similar between cohorts (early: 36.9 [3.5]; late: 36.9 [3.6]). The mean (SD) change in the GAS-T score from baseline to 12 weeks was greater in the early versus late cohort (15.7 [8.9] vs. 13.1 [8.9]; p < 0.001). More patients in the early versus late cohort had a GAS-T score ≥ 50 (63.9% vs. 47.4%; p < 0.001) at 12 weeks. No new safety concerns were reported. Early treatment of PSS with BoNT-A has a positive impact on patients’ ability to achieve treatment goals. Plain Language Summary: After a stroke, people can experience muscle stiffness in their limbs, called post-stroke spasticity (PSS), which can lead to pain and make movement difficult. Treatment can include botulinum toxin A (BoNT-A) injections given directly into affected muscles. The aim of our study was to assess whether giving BoNT-A within a year after experiencing a stroke was more effective in treating PSS than delaying treatment. We combined data from 968 patients across five different studies. Most people (802 patients) received BoNT-A treatment 1 year or more after their stroke (late treatment group), while 166 people received treatment within a year of their stroke (early treatment group). In the studies, patients set treatment goals with their physician, for example being able to hold an object or walk a certain distance. After treatment, the extent to which each goal was achieved was assessed and scored based on whether the result was less than expected, as expected, or better than expected by the patient and physician. The scores from the two treatment groups were compared. People in the early treatment group did better in achieving their treatment goals compared with those in the late treatment group. We also looked at any side effects patients experienced. No unexpected side effects were reported. BoNT-A treatment of PSS can help patients achieve their treatment goals, and patients treated early (within 1 year after stroke) may do better than those treated later. This information may help in rehabilitation planning for stroke patients. Full article

Background: Early local recurrence (ELR) in musculoskeletal sarcoma is associated with poor oncologic outcomes, yet the relative impact of tumor biology versus system-level factors remains insufficiently understood. This multicenter real-world study within the Swiss Sarcoma Network evaluated whether the initial care pathway influences the risk and timing of ELR. Methods: Patients with histologically confirmed sarcoma and documented local recurrence were classified according to initial management within a Comprehensive Care Pathway (CCP) or a Fragmented Care Pathway (FCP). ELR was defined as recurrence within 12 months after index surgery. Associations were analyzed using restricted Cox proportional hazards models and Firth-penalized logistic regression, adjusting for key clinicopathologic factors. Follow-up was calculated from index surgery to death or administrative censoring (median 88.2 months; interquartile range, 54.9–141.6). Results: Among 158 patients with local recurrence, 96 (60.8%) were treated within CCP, and 62 (39.2%) entered through FCP. ELR occurred in 53 patients (33.5%) and was more frequent in the FCP cohort. Fragmented care was independently associated with ELR in both time-to-event analysis (hazard ratio 2.00, 95% CI 1.14–3.51) and penalized logistic regression (odds ratio 2.83, 95% CI 1.09–6.94). Unplanned (“whoops”) procedures and incomplete resection margins were substantially more common in FCP and independently predicted ELR. Tumor grade also contributed to risk, but the magnitude of the pathway effect was comparable. ELR was associated with higher rates of synchronous metastases and inferior survival compared with late local recurrence. Adjuvant therapy did not independently reduce ELR risk after adjustment for surgical quality. Conclusions: These findings indicate that ELR in musculoskeletal sarcoma is strongly influenced by modifiable system-level factors. Early referral, multidisciplinary evaluation, and expert margin-oriented surgery are critical to reducing early recurrence and improving patient outcomes. Full article

Land subsidence constitutes a critical hazard to coastal megacities globally, amplifying flood risks and damaging infrastructure. Taking Tianjin—a major port city underlain by compressible sediments and affected by groundwater over-exploitation—as a case study, we address two key research gaps: the absence of a quantitative framework coupling groundwater extraction with construction land expansion, and the inadequate separation of seasonal and long-term subsidence drivers. We developed an integrated remote-sensing-based approach: high-resolution subsidence time series (2016–2023) were derived via Small BAseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) using Sentinel-1 Synthetic Aperture Radar (SAR) imagery, validated against leveling measurements (R > 0.885, error < 20 mm). This subsidence dataset was fused with groundwater level records and annual construction land maps. Seasonal-Trend Decomposition using Loess (STL) isolated trend, seasonal, and residual components, which were input into a Random Forest (RF) model to quantify the relative contributions of subsidence drivers. Dynamic Time Warping (DTW) and Cross-Wavelet Transform (CWT) were further employed to characterize temporal patterns and lag effects between subsidence and its drivers. Our results reveal a distinct shifting subsidence pattern: “areal expansion but intensity weakening.” Groundwater control policies mitigated five historical subsidence funnels, reducing areas with severe subsidence from 72.36% to <5%, while the total subsiding area expanded by 1024.74 km², with new zones emerging (e.g., northern Dongli District). The RF model identified the long-term groundwater level trend as the dominant driver (59.5% contribution), followed by residual (23.3%) and seasonal (17.2%) components. Cross-spectral analysis confirmed high coherence between subsidence and long-term groundwater trends; the seasonal component exhibited a dominant resonance period of 12 months and a consistent subsidence response lag of 3–4 months. Construction impacts were conceptualized as a “load accumulation-soil compression-time lag” mechanism, with high-intensity engineering projects inducing significant local subsidence. This study provides a robust quantitative framework for disentangling the complex interactions between subsidence, groundwater, and urban expansion, offering critical insights for evidence-based hazard mitigation and sustainable urban planning in vulnerable coastal environments worldwide. Full article

Uric acid is closely related to diseases such as gout, kidney failure, and metabolic disorders. A conventional method for measuring uric acid over 24 h is time intensive and cumbersome for patients who have to take samples to the hospital. At present, hospitals use only laboratory instruments to determine 24-h uric acid concentrations in the urine. This study presents the proof-of-concept of a portable point-of-care tool called Uricia, designed to improve the quality of life of patients monitoring uric acid. Spectrophotometry was performed at a fixed wavelength of 295 nm. The urine sample contained within the cuvette absorbs ultraviolet light, with uric acid specifically responsible for this absorption, thereby allowing the device to measure its concentration. An internal calibration algorithm was used to accommodate the nonlinear optical response of Uricia and was calibrated to a benchtop GENESYS 10S UV–Vis spectrophotometer. The experiments further evaluated potential urinary interferences, revealing that while most constituents had minimal impact, ascorbic acid demonstrated the highest interference, contributing up to 15% of the total signal at high physiological concentrations. This device and the corresponding spectrophotometry method revealed that high concentrations of uric acid precipitated insoluble crystals. A dilution set to an alkali solution vial to be premixed and dissolve the uric acid crystals was added, increasing the detection window to 10 mg/dL, with an LOD of 0.0232 mg/dL and LOQ of 0.0702 mg/dL. Cloud-based data measurement enables spot analysis, which is meant to provide insight into patient status development. These results validated the technical architecture of a controlled matrix for measuring uric acid. Full article