Leiden University Scholary Publications
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Algorithm appreciation or aversion: the effects of accuracy disclosure on users' reliance on algorithmic suggestions
Get PDFPrior work highlights people's tendency to initially overtrust algorithmic decisions, but also disproportionality lower their trust following an algorithm's mistakes. In contrast, people maintain higher trust when they see a human make similar mistakes. We evaluated how communicating accuracy information about an algorithm affected trust behaviour. Participants in Study I (N = 284) and Study II (N = 272) were given estimation tasks, and were provided with an algorithm's estimation as a suggestion. Half the participants received a description of the algorithm along with its average accuracy. During the task, algorithmic errors were introduced systematically, and participants noticed that the algorithm made substantial errors. Our results show that an algorithm's presentation significantly affects participants' reliance. Participants who were given information about the algorithm's accuracy conformed significantly more to the algorithm. Additionally, participants' reactions align with the previously documented algorithm aversion effect. Participants deviated more from the algorithm's estimations after observing the difference in performance between themselves and the algorithm. This resulted in reduced participant performance, as the algorithms were, on average, quite accurate. Furthermore, participants were able to distinguish between correct and incorrect suggestions, which is promising for successful trust calibration.Computer Systems, Imagery and Medi
Landscape changes elevate the risk of avian influenza virus diversification and emergence in the East Asian–Australasian Flyway
Get PDFEnvironmental Biolog
A screening tool to detect interstitial lung disease in systemic sclerosis: the ILD-RISC score
Get PDFObjectivesAs a screening tool for the presence of systemic sclerosis-associated interstitial lung disease (SSc-ILD) on high-resolution computed tomography (HRCT) is missing, we aimed to develop the ILD-RISC score, a risk algorithm to guide physicians in ordering HRCTs, with specific focus on follow-up visits.MethodsThe nominal group technique was used to select items for the multivariable logistic regression with backward selection. The ILD-RISC score was developed from baseline visits of the derivation cohort. After identifying a cut-off favoring sensitivity >85% from the ROC curve, it was validated in a separate cross-sectional cohort, and then applied longitudinally in a specific SSc cohort with negative baseline HRCT.ResultsIn the derivation cohort (533 patients), 13 variables associated with the presence of SSc-ILD on HRCT were tested. The ILD-RISC score, including FVC%, DLCO/SB%, digital ulcers ever, age and SSc autoantibodies, showed an area under the curve of 79.1% (75.3–83.0%) for the presence of SSc-ILD on HRCT. An ILD-RISC score 0.3 had sensitivity 85.6% and specificity 53.6%, as confirmed in the validation cohort (247 patients). Among 819 patients with negative baseline HRCT, 170 developed SSc-ILD: a low ILD-RISC score was detected in almost 50% of the follow-up visits, supporting the sparing of HRCTs.ConclusionThe ILD-RISC score was developed and validated to predict the presence of SSc-ILD. Thus, the ILD-RISC score may help to decide when to order HRCTs at follow-up, allowing the reduction of costs and radiation exposure, but also at the time of SSc diagnosis when resources are limited.Pathophysiology and treatment of rheumatic disease
Distinct lipidomic profiles in breast cancer cell lines relate to proliferation and EMT phenotypes
Get PDFRewiring of lipid metabolism is a hallmark of cancer, supporting tumor growth, survival, and therapy resistance. However, lipid metabolic heterogeneity in breast cancer remains poorly understood. In this study, we systematically profiled the lipidome of 52 breast cancer cell lines using liquid chromatography-mass spectrometry to uncover lipidomic signatures associated with tumor subtype, proliferation, and epithelial-to-mesenchymal (EMT) state. A total of 806 lipid species were identified and quantified across 21 lipid classes. The main lipidomic heterogeneity was associated with the EMT state, with lower sphingolipid, phosphatidylinositol and phosphatidylethanolamine levels and higher cholesterol ester levels in aggressive mesenchymal-like cell lines compared to epithelial-like cell lines. In addition, cell lines with higher proliferation rates had lower levels of sphingomyelins and polyunsaturated fatty acid (PUFA) side chains in phospholipids. Next, changes in the lipidome over time were analyzed for three fast-proliferating mesenchymal-like cell lines MDA-MB-231, Hs578T, and HCC38. Triglycerides decreased over time, leading to a reduction in lipid droplet levels, and especially PUFA-containing triglycerides and -phospholipids decreased during proliferation. These findings underscore the role of EMT in metabolic plasticity and highlight proliferation-associated lipid dependencies that may be exploited for therapeutic intervention. In conclusion, our study reveals that EMT-driven metabolic reprogramming is a key factor in lipid heterogeneity in breast cancer, providing new insights into tumor lipid metabolism and potential metabolic vulnerabilities.Toxicolog
Neural correlates of loudness coding in two types of cochlear implants-A model study
Get PDFMany speech coding strategies have been developed over the years, but comparing them has been convoluted due to the difficulty in disentangling brand-specific and patient-specific factors from strategy-specific factors that contribute to speech understanding. Here, we present a comparison with a 'virtual' patient, by comparing two strategies from two different manufacturers, Advanced Combination Encoder (ACE) versus HiResolution Fidelity 120 (F120), running on two different implant systems in a computational model with the same anatomy and neural properties. We fitted both strategies to an expected T-level and C- or M-level based on the spike rate for each electrode contact's allocated frequency (center electrode frequency) of the respective array. This paper highlights neural and electrical differences due to brand-specific characteristics such as pulse rate/channel, recruitment of adjacent electrodes, and presence of subthreshold pulses or interphase gaps. These differences lead to considerably different recruitment patterns of nerve fibers, while achieving the same total spike rates, i.e., loudness percepts. Also, loudness growth curves differ significantly between brands. The model is able to demonstrate considerable electrical and neural differences in the way loudness growth is achieved in CIs from different manufacturers.Disorders of the head and nec
Introduction of oikography
No full textWhether one is in front of the camera or behind it, inside their home or outside their house, photographs have proven indispensable in probing into the idea of home. In a time when displacement, migration, and homelessness have become commonplace due to geopolitical conflicts and oppressive ideologies, the role of photography in exploring the process of homemaking has become an irrefutable fact of sociopolitical debates. With that in mind, how can a representational medium deal with home as something that is not necessarily limited to the photographic frame? In other words, can photography embody the emotional and interpersonal aspects of home as well as participate in the social, political, and cultural debates on homemaking? Echoing the word photography, which is a compound of ph.tós (light) and graphé (writing/drawing), this book defines “oikography” (oikos + graphé) as “homemaking through photography”. Following the same logic, it considers “oikographs” as photographs whose principal function is twofold: reflecting on the idea of home and dwelling on the process of homemaking. With the concept of home at its methodological and theoretical core, Oikography aims to show how photography envisages, embodies and apperceives home as a spatial idea, regardless of whether that space is idealized or ideologized, ontologized or theorized, materialized or dematerialized, territorialized or deterritorialized, or internalized within us or externalized around us. To this end, Oikography asks: How can photography represent the lived, perceived, and conceived experiences of homemaking?Modern and Contemporary Studie
Causal inference approaches reveal associations between LDL oxidation, NO metabolism, telomere length and DNA integrity within the MARK-AGE study
Get PDFGenomic instability markers are important hallmarks of aging, as previously evidenced within the European study of biomarkers of human aging, MARK-AGE; however, establishing the specific metabolic determinants of vascular aging is challenging. The objective of the present study was to evaluate the impact of the susceptibility to oxidation of serum LDL particles (LDLox) and the plasma metabolization products of nitric oxide (NOx) on relevant genomic instability markers. The analysis was performed on a MARK-AGE cohort of 1326 subjects (635 men and 691 women, 35-75 years old) randomly recruited from the general population. The Inverse Probability of Treatment Weighting causal inference algorithm was implemented in order to assess the potential causal relationship between the LDLox and NOx octile-based thresholds and three genomic instability markers measured in mononuclear leukocytes: the percentage of telomeres shorter than 3 kb, the initial DNA integrity, and the DNA damage after irradiation with 3.8 Gy. The results showed statistically significant telomere shortening for LDLox, while NOx yielded a significant impact on DNA integrity. Overall, the effect on the genomic instability markers was higher than for the confirmed vascular aging determinants, such as low HDL cholesterol levels, indicating a meaningful impact even for small changes in LDLox and NOx values.Molecular Epidemiolog
Machine learning-based model selection and averaging outperform single-model approaches for a priori vancomycin precision dosing
Get PDFSelecting an appropriate population pharmacokinetic (PK) model for individual patients in model-informed precision dosing (MIPD) can be challenging, particularly in the absence of therapeutic drug monitoring (TDM) samples. We developed a machine learning (ML) model to guide individualized PK model selection for a priori MIPD of vancomycin based on routinely recorded patient characteristics. This retrospective analysis included 343,636 vancomycin TDM records, each from a distinct adult patient across 156 healthcare centers, along with a priori predictions from six PK models. A multi-label classification approach was applied, labeling PK model predictions based on whether they fell within 80%-125% of observed TDM values. Various modeling strategies were evaluated using XGBoost as the base algorithm, with binary relevance selected for the final model. At the prediction stage, PK models were ranked and averaged for each patient based on ML-predicted probabilities that predictions would fall within 80%-125% of the observed concentration. Selecting the highest ranked PK model for each patient and ML-based model averaging outperformed all single PK models, body mass index-based selection, and naive averaging. On a population level, these ML approaches resulted in more accurate predictions, a higher proportion of predictions within 80%-125% of observed vancomycin concentrations, and no systematic bias. Predictive performance declined with lower ML-assigned rankings, and selecting the lowest-ranked PK model for each patient resulted in worse performance than the worst-performing single PK model. By guiding the selection of appropriate models and avoiding less suitable ones, ML approaches for a priori MIPD may improve early dosing decisions.Pharmacolog
