Level Of Complexity Research Articles

Soft, crispy, crunchy, sustainable: The role of visual textures in shaping sustainable food preferences

This research evaluates the potential of using visual textural complexity as a subtle yet effective strategy to direct consumer preferences towards more sustainable food choices, addressing the urgent need to reduce greenhouse gas emissions in the food industry.Using a traditional Turkish rice pudding, sütlaç, as a case study, we prepared four variants with varying textural complexities (ranging from simple to complex) by reducing the portion size by half and gradually adding soft, crispy, crunchy, and airy textured food layers onto it. Two parallel sets of variants were formulated to minimize potential bias from differences in composition and visual properties of the layers. One hundred participants individually evaluated paired visual stimuli of these variants under two experimental conditions: non-informative, which included only visuals, and informative, which included visuals with accompanied by sample information.Paired binary analysis revealed consistent preference for variants with higher levels of visual textural complexity, especially those with three layers (soft, crispy and crunchy), regardless of experimental conditions and product formulations. Although sample information affected preference scores, variants with certain levels of textural complexity were still preferred over the traditional sample (p < 0.05). Preferences for sample variants over the control reduced the carbon emission over 31 %. The study links the impact of visual textural complexity on preferences to the Elaboration Likelihood Model (ELM) and demonstrates that this strategy can effectively direct consumer preferences towards more sustainable options. Adopting the insights from this study can assist food producers and marketers in contributing to the broader goal of reducing carbon emissions.

Integrated top-down process and voxel-based microstructure modeling for Ti-6Al-4 V in laser wire direct energy deposition process

Laser-wire metal additive manufacturing (AM) is one of the ideal direct energy deposition (DED) processes for creating large-scale parts with a medium level of complexity. However, the DED process involves complex thermal signatures and wide length scales making the fabrication of realistic AM components and part qualification often reliant on experimental trial-and-error optimization. While experimental measurements over the full volume of a part are valuable and necessary, measuring the entire area of a part is significantly laborious and practically infeasible, particularly for large parts in terms of cost and rapid qualification. Therefore, in this work, we developed an effective thermal and microstructure modeling framework based on the Johnson–Mehl-Avrami-Kolmogorov (JMAK) and Koistinen & Marburger (KM) models through a top-down approach that considers plate distortion-affected thermal profiles. A voxel-by-voxel simulation method is used to predict individual phase fractions of Ti-6Al-4 V. The predicted results were validated through detailed metallurgical measurements. A combined voxel-by-voxel approach with a sparse data reconstruction technique produced a near-perfect reconstruction of the original data. This approach anticipates a significant reduction in data points and computation time and resources. Lastly, we conclude with potential extensions of this work to other modeling efforts.

TGF-β Signaling Loop in Pancreatic Ductal Adenocarcinoma Activates Fibroblasts and Increases Tumor Cell Aggressiveness.

The interaction between cancer cells and cancer-associated fibroblasts (CAFs) is a key determinant of the rapid progression, high invasiveness, and chemoresistance of aggressive desmoplastic cancers such as pancreatic ductal adenocarcinoma (PDAC). Tumor cells are known to reprogram fibroblasts into CAFs by secreting transforming growth factor beta (TGF-β), amongst other cytokines. In turn, CAFs produce soluble factors that promote tumor-cell invasiveness and chemoresistance, including TGF-β itself, which has a major role in myofibroblastic CAFs. Such a high level of complexity has hampered progress toward a clear view of the TGFβ signaling loop between stromal fibroblasts and PDAC cells. Here, we tackled this issue by using co-culture settings that allow paracrine signaling alone (transwell systems) or paracrine and contact-mediated signaling (3D spheroids). We found that TGF-β is critically involved in the activation of normal human fibroblasts into alpha-smooth muscle actin (α-SMA)-positive CAFs. The TGF-β released by CAFs accounted for the enhanced proliferation and resistance to gemcitabine of PDAC cells. This was accompanied by a partial epithelial-to-mesenchymal transition in PDAC cells, with no increase in their migratory abilities. Nevertheless, 3D heterospheroids comprising PDAC cells and fibroblasts allowed monitoring the pro-invasive effects of CAFs on cancer cells, possibly due to combined paracrine and physical contact-mediated signals. We conclude that TGF-β is only one of the players that mediates the communication between PDAC cells and fibroblasts and controls the acquisition of aggressive phenotypes. Hence, these advanced in vitro models may be exploited to further investigate these events and to design innovative anti-PDAC therapies.

The pivotal role of clinical tutorial teaching in knowledge construction.

Students' new knowledge is gradually built up in the context of the task for which it is required and consolidated by applying it to clinical cases. As students see more and more clinical cases the knowledge emerges from an associative mesh of different levels of understanding. During tutorial clinical teaching, residents should be gradually exposed to an increasing range of real-world learning tasks and increasing levels of complexity. This exposure allows them to gradually develop shortcuts in the retrieval of their knowledge. This commentary provides a rationale for the construction of knowledge and the pivotal role that clinical tutorial teaching plays in this task.

Co-Designing Dynamic Mixed Reality Drill Positioning Widgets: A Collaborative Approach with Dentists in a Realistic Setup.

Mixed Reality (MR) is proven in the literature to support precise spatial dental drill positioning by superimposing 3D widgets. Despite this, the related knowledge about widget's visual design and interactive user feedback is still limited. Therefore, this study is contributed to by co-designed MR drill tool positioning widgets with two expert dentists and three MR experts. The results of co-design are two static widgets (SWs): a simple entry point, a target axis, and two dynamic widgets (DWs), variants of dynamic error visualization with and without a target axis (DWTA and DWEP). We evaluated the co-designed widgets in a virtual reality simulation supported by a realistic setup with a tracked phantom patient, a virtual magnifying loupe, and a dentist's foot pedal. The user study involved 35 dentists with various backgrounds and years of experience. The findings demonstrated significant results; DWs outperform SWs in positional and rotational precision, especially with younger generations and subjects with gaming experiences. The user preference remains for DWs (19) instead of SWs (16). However, findings indicated that the precision positively correlates with the time trade-off. The post-experience questionnaire (NASA-TLX) showed that DWs increase mental and physical demand, effort, and frustration more than SWs. Comparisons between DWEP and DWTA show that the DW's complexity level influences time, physical and mental demands. The DWs are extensible to diverse medical and industrial scenarios that demand precision.

Comparative cytotoxicity and mitochondrial disruption in H9c2 cardiomyocytes induced by common pesticides

Chronic exposure to pesticides is believed to be associated with various human diseases, including cardiovascular diseases. However, the mechanisms by which pesticides lead to cardiovascular diseases remain unclear. In our study, we selected the following commonly used pesticides as typical examples: the herbicides glyphosate (GLY) and glufosinate ammonium (GLA); the insecticides imidacloprid (IMI) and thiamethoxam (THM); and the fungicides pyraclostrobin (PYR) and azoxystrobin (AZO). We employed H9c2 cells as a model to investigate the cytotoxic effects of these pesticides on myocardial cells at concentrations of 1, 10, 100, and 1000 mg/L. The results indicate that these pesticides can affect cell viability, alter the cell cycle, and significantly impact ATP content and mitochondrial complex levels, ultimately triggering oxidative stress responses in the cells. However, compared to herbicides GLY and GLA, insecticides IMI and THM, and fungicides PYR and AZO pesticides are more toxic to H9c2 cells. Additionally, GLY, GLA, IMI, THM, PYR, and AZO were found to cause structural changes in the mitochondria of H9c2 cells. Molecular docking results suggest that these pesticides can bind to proteins related to mitochondrial dynamics. Furthermore, IMI, THM, PYR, and AZO exhibit stronger binding abilities to mitochondrial dynamics-related proteins. These findings indicate that these pesticides significantly adverse effects on myocardial cells, mainly by causing mitochondrial dysfunction and inducing oxidative stress. Our findings highlight the importance of considering the differential toxicity of various classes of pesticides when assessing their risks to human health, particularly concerning cardiovascular diseases.

Dynamics of Respiratory Rate and Heart Rate Variability when Performing a Cognitive Task of Two Levels of Complexity

The study examined heart rate variability (HRV) and respiratory rate during a cognitive task (reading) at two difficulty levels. Time, frequency and nonlinear analysis of HRV was used. It has been shown that both some indicators of HRV (HR, SDNN, RMSSD, SD2, SD2/SD1) and respiratory rate change with increasing mental load, however, they do not separately demonstrate significant differences at all three stages of the study. Therefore, for the first time for cognitive studies, an integral indicator was used that links the parameters of the heart with respiration – the physiological cost of activity (PhysCost), which was previously used in work with athletes when they performed physical exercises to failure. Changes in the PhysCost showed that differences between a simple and a complex task are observed at all stages of the study. Thus, it has been established that the difference in the functional state of a person in the process of performing a continuous task of two levels of complexity is most reliably revealed when using an integrative indicator connecting the activity of the respiratory system and the circulatory system.

Evolvability in Artificial Development of Large, Complex Structures and the Principle of Terminal Addition.

Epigenetic tracking (ET) is a model of development that is capable of generating diverse, arbitrary, complex three-dimensional cellular structures starting from a single cell. The generated structures have a level of complexity (in terms of the number of cells) comparable to multicellular biological organisms. In this article, we investigate the evolvability of the development of a complex structure inspired by the "French flag" problem: an "Italian Anubis" (a three-dimensional, doglike figure patterned in three colors). Genes during development are triggered in ET at specific developmental stages, and the fitness of individuals during simulated evolution is calculated after a certain stage. When this evaluation stage was allowed to evolve, genes that were triggered at later stages of development tended to be incorporated into the genome later during evolutionary runs. This suggests the emergence of the property of terminal addition in this system. When the principle of terminal addition was explicitly incorporated into ET, and was the sole mechanism for introducing morphological innovation, evolvability improved markedly, leading to the development of structures much more closely approximating the target at a much lower computational cost.

An Evaluation of the Estimated Aligners Needed to Correct Malocclusion Traits Using Invisalign ClinCheck™ Pro Software: A Retrospective Study.

Background: This study evaluated the number of aligners that Invisalign ClinCheck™ Pro Software estimates for correcting different malocclusion traits. Methods: This retrospective study included 157 non-extraction patients over the age of 12 years old with easy to mild malocclusions who were treated with Invisalign aligners. The Index of Complexity, Outcome, and Need (ICON) was used to evaluate the malocclusion complexity level. The number of aligners (upper, lower, and total) required to correct the malocclusion was compared based on sex, ICON level, molar and canine class, occlusal asymmetry, overbite, overjet, crowding, incisor inclination, and Bolton discrepancy. A Mann-Whitney U test (for comparisons between two groups) or a Kruskal-Wallis test (for comparisons between three or more groups) (p < 0.05) was used to evaluate differences in the number of aligners across variable categories. Results: ICON, molar class, overbite, and overjet presented significant differences (p < 0.05) in the number of aligners (upper, lower, and total) required to correct a malocclusion. Canine class and lower dental crowding showed significant differences in the lower and total number of aligners (p < 0.05). Conclusions: The number of aligners increases when the malocclusion presents any of the following elements: the absence of molar or canine class I, an altered overjet or overbite, severe lower crowding, or a higher complexity level. The clinician should consider these malocclusion traits when estimating the number of aligners needed for correction.

Comparative Real-Time Study of Three Enhanced Control Strategies Applied to Dynamic Process Systems

In this study, a comparative analysis of three different control methods for precise, real-time control of a complex dynamic double-tank liquid level process system was performed. Since the system in question has a time-delayed structure, feedforward proportional integral (FF-PI) control and cascaded nonlinear feedforward proportional integral delayed (CNPIR) controllers were tested on the process system. While the FF-PI controller improved the response time of the system, it showed limitations in handling external disturbances and nonlinearities. On the other hand, the CNPIR controller showed better improvements in control accuracy and lower overshoot compared to the FF-PI controller. Since the process system has a nonlinear model and is affected by external disturbances, these two controllers were inadequate in this study when compared to the fractional order adaptive proportional integral derivative sliding mode controller (FO-APIDSMC). The FO-APIDSMC controller provided fairly good performance in both tracking accuracy and disturbance rejection control for non-chattering, fast finite-time convergence, increased robustness, and uncertain dynamic processes. Experimental results reveal that the FO-APIDSMC controller achieves superior minimized tracking error and outperforms the FF-PI and CNPIR controllers by effectively handling uncertainties and external disturbances.

Power Quality State Estimation for Distribution Grids Based on Physics-Aware Neural Networks—Harmonic State Estimation

In the transition from traditional electrical energy generation with mainly linear sources to increasing inverter-based distributed generation, electrical power systems’ power quality requires new monitoring methods. Integrating a high penetration of distributed generation, which is typically located in medium- or low-voltage grids, shifts the monitoring tasks from the transmission to distribution layers. Compared to high-voltage grids, distribution grids feature a higher level of complexity. Monitoring all relevant nodes is operationally infeasible and costly. State estimation methods provide knowledge about unmeasured locations by learning a physical system’s non-linear relationships. This article examines a new flexible, close-to-real-time concept of harmonic state estimation using synchronized measurements processed in a neural network. A physics-aware approach enhances a data-driven model, taking into account the structure of the electrical network. An OpenDSS simulation generates data for model training and validation. Different load profiles for both training and testing were utilized to increase the variance in the data. The results of the presented concept demonstrate high accuracy compared to other methods for harmonic orders 1 to 20.

Team roles and challenges in experiential learning in sustainability accounting education: A four-stage learning cycle

ABSTRACT This study aims to provide insights into the process of team-based experiential learning in a sustainability accounting course. A case study of a postgraduate course on material flow cost accounting at a German university was applied. Data were collected from learning journals and in-depth interviews. The findings provide insights into the process of team-based experiential learning. The process is indicated by four team roles of students: interpersonal, information, analytic, and action roles, which move around the four-stage learning cycle. Six challenges in students' experiential learning in teams were found at different stages: the characteristics of team dynamics, the selection of relevant information from the case, confusion and frustration, connecting information in a meaningful manner, time constraints, and the increasingly complex level of the tasks. The study contributes to the accounting education literature and experiential learning literature by extending knowledge about team roles and learning challenges around the learning cycle. Practical implications for educators are discussed to facilitate team-based experiential learning toward sustainability education. These include the adoption of educator role profiles to support students' learning, the creation of a safe learning space for students, and the design of experiential learning activities on the foundation of four-stage learning processes.

MTORC1 and mTORC2 Levels in Patients With Psoriasis

Introduction: In recent years, the role of the mammalian target of rapamycin (mTOR) pathway, which is one of the intracellular signaling pathways and known as the main control pathway of metabolism, in the pathogenesis of psoriasis has been emphasized. Objectives: We sought to investigate the importance of the mTOR pathway in the pathogenesis of psoriasis. Methods: Forty patients with psoriasis and 40 healthy volunteers were included in this case-control study. Serum fasting mTORC1 and mTORC2 levels of the study groups were examined by enzyme-linked immunosorbent assay. Results: Serum mTORC1 and mTORC2 levels were significantly lower in patients with psoriasis than controls (p= 0.001). A positive correlation was found between serum mTORC1 and serum mTORC2 levels in patients with psoriasis (p=0,001, r=0,826). Conclusion: The lower serum levels of mTORC1 and mTORC2 complexes which are active signalling molecules in the cell, were found to be lower in patient with psoriasis, suggesting that it may be an indicator of increased intracellular activation of these molecules. Our opinion that agents that can effectively inhibit both mTOR complexes may be more effective in the treatment of psoriasis.

Evaluation of durum and hard red spring wheat panels for sensitivity to necrotrophic effectors produced by Parastagonospora nodorum.

Septoria nodorum blotch is an important disease of both durum and hard red spring wheat (HRSW) worldwide. The disease is caused by the necrotrophic fungal pathogen Parastagonospora nodorum when compatible gene-for-gene interactions occur between pathogen-produced necrotrophic effectors (NEs) and corresponding host sensitivity genes. To date, nine sensitivity gene-NE interactions have been identified, but there is little information available regarding their overall frequency in durum and HRSW. Here, we infiltrated a global HRSW panel (HRSWP) and the Global Durum Panel (GDP) with P. nodorum NEs SnToxA, SnTox1, SnTox267, SnTox3, and SnTox5. Frequencies of sensitivity to SnTox1 and SnTox5 were higher in durum compared to HRSW and vice versa for SnTox267 and SnTox3. Strong associations for the known sensitivity loci Tsn1, Snn1, Snn2, Snn3, Snn5, and Snn7 along with potentially novel sensitivity loci on chromosome arms 7DS and 3BL associated with SnToxA and SnTox267, respectively, were identified in the HRSWP. In the GDP, Snn1, Snn3, and Snn5 were identified along with novel loci associated with sensitivity to SnTox267 on chromosome arms 2AS, 2AL, and 6AS and with SnTox5 sensitivity on 2BS and 7BL. These results reveal additional NE sensitivity loci beyond those previously described demonstrating a higher level of genetic complexity of the wheat-P. nodorum system than previously thought. Knowledge regarding the prevalence and genomic locations of SNB susceptibility genes in HRSW and durum will prove useful for developing efficient breeding strategies and improving varieties for SNB resistance.

Bio-inspired space-filling fractal metamaterial

Inspired by mammal cranial sutures with spatiotemporal morphological variation, two-phase space-filling fractal metamaterial was designed. Designs with different levels of complexity are fabricated via multi-material polymer jetting. Mechanical tests and systematic finite element (FE) simulations are conducted to evaluate the mechanical performance of the designs. It is found that the hierarchical number N of two-phase space-filling fractal metamaterial played an important role in their mechanical behaviors. The experimental results show that with increasing the hierarchical number N, these metamaterials show enhanced stiffness, strength, and toughness under tensile tests. From the simulation results, we found by decoupling the strain energy density in two phases, with increasing N, the soft phase has contributed almost the same energy level, however, the hard phase has contributed increasing energy level. Moreover, we found the volume fraction and the stiffness ratio of the hard phase dominate the overall mechanical properties of these two-phase space-filling fractal metamaterial. The bio-inspired mechanical metamaterials have broad applications in engineering materials for dissipating energy dissipation, mitigating impact, and retarding damages.

NRO-stylization: A novel algorithm for regular octahedral stylization aesthetic modeling of three-dimensional surface mesh

Stylization of 3D shapes has been a prominent topic in computer graphics. Geometric stylization, as a category within 3D shape stylization, has garnered widespread attention due to its distinctive geometric aesthetics. This paper introduces a novel and simplified method for achieving regular octahedral stylization, capable of transforming the input shape into the regular octahedral style while preserving the content of the original shape. The proposed method achieves regular octahedral stylization by using face normals. Its implementation is straightforward because it incurs a cost only in terms of solving several linear systems. To demonstrate the effectiveness and robustness of the proposed method, extensive tests were conducted on models with varying levels of complexity and topological structures. The results highlight the exceptional capability of the proposed method to generate geometric shapes with an aesthetically pleasing regular octahedral style.

Monte Carlo damage models of different complexity levels predict similar trends in radiation induced DNA damage

Ion therapies have an increased relative biological effectiveness (RBE) compared to X-rays, but this remains poorly quantified across different radiation qualities. Mechanistic models that simulate DNA damage and repair after irradiation could be used to help better quantify RBE. However, there is large variation in model design with the simulation detail and number of parameters required to accurately predict key biological endpoints remaining unclear. This work investigated damage models with varying detail to determine how different model features impact the predicted DNA damage.&#xD;&#xD;Methods: Damage models of reducing detail were designed in TOPAS-nBio and Medras investigating the inclusion of chemistry, realistic nuclear geometries, single strand break damage, and track structure. The nucleus models were irradiated with 1 Gy of protons across a range of linear energy transfers (LETs). Damage parameters in the models with reduced levels of simulation detail were fit to proton double strand break (DSB) yield predicted by the most detailed model. Irradiation of the optimised models with a range of radiation qualities was then simulated, before undergoing repair in the Medras biological response model.&#xD;&#xD;Results: Simplified damage models optimised to proton exposures predicted similar trends in DNA damage across radiation qualities. On average across radiation qualities, the simplified models experienced an 8% variation in double strand break (DSB) yield but a larger 28% variation in chromosome aberrations. Aberration differences became more prominent at higher LETs, with model features having an increasing impact on the distribution and therefore misrepair of DSBs. However, overall trends remained similar with better agreement likely achievable through repair model optimisation. &#xD;&#xD;Conclusion: Several model simplifications could be made without compromising key damage yield predictions, although changes in damage complexity and distribution were observed. This suggests simpler, more efficient models may be sufficient for initial radiation damage comparisons, if validated against experimental data.&#xD.

The New Healthcare: AI-Driven Population Stratification, Proactive Medicine, and Predictive Analysis

Abstract Background The Covid-19 pandemic has highlighted structural and functional weakness of local health services. Italy carried out its reorganization with DM 77/2022, financed by Mission 6 PNRR of the CE. The model adopted aims to move from a reactive to proactive medicine, to be implemented close to the places where citizens live. The priority objective is to know data on the progress of chronic pathologies and non self-sufficiency using advanced digitalization tools. Methods 14 types of administrative data from 2022 to 2023, concerning 180000 (ISTAT data) people in the Lecce Social Health District (DSS Lecce), were analyzed with AI (Chat GPT). Results Thanks to algorithms, 6 categories of clinical complexity were identified. The analysis showed that the population assisted is 198696, for temporary presences, with the most represented age group being 50-55 years. Births decreased by 36% in 10 years (from 1681 to 1076), with 2197 deaths in 2023. 42,38% of the population (average age 38,58 years) did not use healthcare resources, while 57,62% (average age 54,19 years) required them. 48646 patients have cardiovascular disease, but only 10% with heart failure were actively monitored. 25047 have metabolic disease, 11195 are diabetics, 5929 have chronic respiratory diseases, 8167 chronic neurological diseases and 907 are cancer patients. Increasing age leads to polymorbidity and show signs of social, economic and health fragility. Conclusions the strategic objective of the Lecce DSS was management of chronicity according to specific care pathways, PDTA. Create healthcare teams capable of being case managers depending on the level of complexity (family doctors, nurses, etc). With the 2024 data there will be 3 consecutive years of analysis which will allow the development of predictive systems to identify population clusters at risk of increasing complexity and in need of proactive medical interventions, use of telemedicine with the support of a Territorial Operations Center. Key messages • AI-driven stratification supports personalized health plans to improve healthcare delivery, patient outcomes, and optimize resource allocation. • A new model of Population Health Management supported by Artificial Intelligence.

A multi-trait embodied framework for the evolution of brains and cognition across animal phyla.

Among non-human animals, crows, octopuses and honeybees are well-known for their complex brains and cognitive abilities. Widening the lens from the idiosyncratic abilities of exemplars like these to those of animals across the phylogenetic spectrum begins to reveal the ancient evolutionary process by which complex brains and cognition first arose in different lineages. The distribution of 35 phenotypic traits in 17 metazoan lineages reveals that brain and cognitive complexity in only three lineages (vertebrates, cephalopod mollusks, and euarthropods) can be attributed to the pivotal role played by body, sensory, brain and motor traits in active visual sensing and visuomotor skills. Together, these pivotal traits enabled animals to transition from largely reactive to more proactive behaviors, and from slow and two-dimensional motion to more rapid and complex three-dimensional motion. Among pivotal traits, high-resolution eyes and laminated visual regions of the brain stand out because they increased the processing demands on and the computational power of the brain by several orders of magnitude. The independent acquisition of pivotal traits in cognitively complex (CC) lineages can be explained as the completion of several multi-trait transitions over the course of evolutionary history, each resulting in an increasing level of complexity that arises from a distinct combination of traits. Whereas combined pivotal traits represent the highest level of complexity in CC lineages, combined traits at lower levels characterize many non-CC lineages, suggesting that certain body, sensory and brain traits may have been linked (the trait-linkage hypothesis) during the evolution of both CC and non-CC lineages.

Variability in patient-reported outcomes among different congenital heart defects: a comparative analysis of 7,498 patients from 32 countries

Abstract Background Patient-reported outcomes (PROs) may not always correlate with the complexity of congenital heart defects (CHDs), as significant variation has been observed between CHDs within complexity levels. Accurate comparisons across various types of CHDs necessitate large sample sizes. Purpose The objective of this study was to compare PROs across different CHDs in a large international sample. Methods ‘Assessment of Patterns of Patient-Reported Outcomes in Adults with Congenital Heart disease – International Study II’ (APPROACH-IS II) was an international cross-sectional investigation, in which 8,415 patients from 32 countries in 6 continents were enrolled (20 high; 7 upper-middle; 4 lower-middle; and 1 low income). For the comparison across different CHDs, conditions with at least 50 patients were included in the analysis. Hence, the sample consisted of 7,498 patients (median age=33y; 53.1% women). Patients completed questionnaires to measure perceived health status (RAND-12 Health Survey; EuroQOL-5D Visual Analog Scale); depressive symptoms (Patient Health Questionnaire-8); anxiety (General Anxiety Disorder-7) and quality of life (Linear Analog Scale). Generalized linear mixed models (GLMMs) were performed with center as random effect. Results Cyanotic heart defects were associated with the lowest scores for physical functioning, mental health, self-rated health, and quality of life (see Figure). Other CHDs found to be associated with poor PRO scores encompassed unrepaired secundum atrial septal defect, Ebstein anomaly, single ventricle, and truncus arteriosus. Conversely, the most favorable scores for all PROs, except for anxiety, were observed with isolated pulmonic stenosis. Other CHDs with favorable PRO scores comprised coarctation of the aorta, isolated small ventricular septal defect, congenital aortic valve disease, and repaired ventricular septal defect. Adjusted for sociodemographic and physiological factors, GLMMs revealed significant differences across defects, using the best score for each PRO as the reference (see Figure). Conclusion Substantial variation in PROs was observed among different types of CHDs. Interestingly, some complex heart defects demonstrated relatively good PRO scores, comparable to some simple defects. On the other hand, unrepaired simple defects or those with residual lesions, were associated with worse PROs.