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Colour and space are pervasive topics in both perception and art. This article investigates the role of colour and pattern in relation to space and time in the art works by two artists: Frank Stella, a well-known Post-War American abstract painter, and Pieter Vermeersch, an emerging Belgian abstract painter, representing a contemporary trend to break the barriers between artistic disciplines. While Stella adheres to the Modernist logic of non-illusionistic, non-spatial, non-referential art as object, perceived instantaneously, Vermeersch explores ways to enhance the viewers’ spatial and temporal experiences through complex art installations with multiple objects and architectural elements interacting with each other and with the spaces in which they are embedded. We discuss these major themes in some representative art works, and in the way they are perceived and appreciated by contemporary viewers, investigated in four empirical studies: two laboratory experiments using well-controlled stimuli derived from at works, and two museum studies employing a variety of methods, including mobile eye-tracking and questionnaires.

Background: In adult patients with sepsis or septic shock admitted to the emergency department, a single intravenous 15 mg/kg amikacin dose provides inadequate pharmacokinetic-pharmacodynamic target attainment at the locally reported minimum inhibitory concentration (MIC) of 2 mg/L and the European Committee on Antimicrobial Susceptibility Testing clinical breakpoint for Enterobacterales of 8 mg/L., Objectives: To provide an amikacin dosing strategy with a clinically acceptable probability of target attainment (PTA) for all patients., Methods: Stochastic simulations were performed using a two-compartment population pharmacokinetics model of amikacin (NONMEM 7.5). PTA was evaluated for various dosing strategies across a range of virtual patients' body weight, body mass index, serum total protein, serum sodium, fluid balance, and estimated glomerular filtration rate according to the Chronic Kidney Disease Epidemiology Collaboration equation (eGFRCKD-EPI), at the locally reported MIC of 2 mg/L and the clinical breakpoint of 8 mg/L. The pharmacokinetic-pharmacodynamic targets were a 24-hour area under the concentration-time curve (AUC24h)/MIC of ≥80 and a 24-hour postdose concentration (C24h) of < 3 mg/L for efficacy and safety, respectively., Results: The PTA for the clinical breakpoint of 8 mg/L was <90% with standard 15 mg/kg dosing, across all patient characteristics. A flat 1500-mg dose achieved ≥90% PTA for the entire population at a MIC of 2 mg/L. However, at the clinical breakpoint of 8 mg/L, a flat 3500-mg dose provided ≥90% PTA only when the eGFRCKD-EPI was <96 mL/min/1.73 m2. The C24h was similar for 1500 mg and 15 mg/kg dosing, whereas 3500 mg resulted in a higher C24h., Conclusions: A flat dose is recommended over weight-based dosing. However, selecting a 1500-mg or 3500-mg dose may compromise either efficacy (MIC 2 mg/L) or safety (clinical breakpoint 8 mg/L), posing a dilemma. Clinical validation is warranted., Competing Interests: I. Spriet received consultancy support and lecture fees from argenx, Pfizer, Merck, and Cidara. E. Dreesen received consultancy fees from Alimentiv and argenx, lecture fees from Celltrion and Galapagos, and financial support from Janssen, R-Biopharm, and Prometheus (all honoraria/fees paid to the University). The remaining authors declare no conflict of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Many patients do not receive a comprehensive medication reconciliation, mostly owing to limited resources. We hence need an approach to identify those patients at the emergency department (ED) who are at increased risk for clinically relevant discrepancies., Objective: The aim of our study was to develop and externally validate a prediction model to identify patients at risk for at least 1 clinically relevant medication discrepancy upon ED presentation., Methods: A prospective, multicenter, observational study was conducted at the University Hospitals Leuven and General Hospital Sint-Jan Brugge-Oostende AV, Belgium. Medication histories were obtained from patients admitted to the ED between November 2017 and May 2022, and clinically relevant medication discrepancies were identified. Three distinct datasets were created for model development, temporal external validation, and geographic external validation. Multivariable logistic regression with backward stepwise selection was used to select the final model. The presence of at least 1 clinically relevant discrepancy was the dependent variable. The model was evaluated by measuring calibration, discrimination, classification, and net benefit., Results: We included 824, 350, and 119 patients in the development, temporal validation, and geographic validation dataset, respectively. The final model contained 8 predictors, for example, age, residence before admission, number of drugs, and number of drugs of certain drug classes based on Anatomical Therapeutic Chemical coding. Temporal validation showed excellent calibration with a slope of 1.09 and an intercept of 0.18. Discrimination was moderate with a c-index (concordance index) of 0.67 (95% CI 0.61-0.73). In the geographic validation dataset, the calibration slope and intercept were 1.35 and 0.83, respectively, and the c-index was 0.68 (95% CI 0.58-0.78). The model showed net benefit over a range of clinically reasonable threshold probabilities and outperformed other selection criteria., Conclusions: Our software-implemented prediction model shows moderate performance, outperforming random or typical selection criteria for medication reconciliation. Depending on available resources, the probability threshold can be customized to increase either the specificity or the sensitivity of the model., (©Greet Van De Sijpe, Matthias Gijsen, Lorenz Van der Linden, Stephanie Strouven, Eline Simons, Emily Martens, Nele Persan, Veerle Grootaert, Veerle Foulon, Minne Casteels, Sandra Verelst, Peter Vanbrabant, Sabrina De Winter, Isabel Spriet. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.11.2024.)

Identifying cell type-specific enhancers in the brain is critical to building genetic tools for investigating the mammalian brain. Computational methods for functional enhancer prediction have been proposed and validated in the fruit fly and not yet the mammalian brain. We organized the 'Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Species Multi-Omics' to assess machine learning and feature-based methods designed to nominate enhancer DNA sequences to target cell types in the mouse cortex. Methods were evaluated based on in vivo validation data from hundreds of cortical cell type-specific enhancers that were previously packaged into individual AAV vectors and retro-orbitally injected into mice. We find that open chromatin was a key predictor of functional enhancers, and sequence models improved prediction of non-functional enhancers that can be deprioritized as opposed to pursued for in vivo testing. Sequence models also identified cell type-specific transcription factor codes that can guide designs of in silico enhancers. This community challenge establishes a benchmark for enhancer prioritization algorithms and reveals computational approaches and molecular information that are crucial for the identification of functional enhancers for mammalian cortical cell types. The results of this challenge bring us closer to understanding the complex gene regulatory landscape of the mammalian brain and help us design more efficient genetic tools and potential gene therapies for human neurological diseases., Competing Interests: Declaration of interests: None declared.

Joint profiling of chromatin accessibility and gene expression in individual cells provides an opportunity to decipher enhancer-driven gene regulatory networks (GRNs). Here we present a method for the inference of enhancer-driven GRNs, called SCENIC+. SCENIC+ predicts genomic enhancers along with candidate upstream transcription factors (TFs) and links these enhancers to candidate target genes. To improve both recall and precision of TF identification, we curated and clustered a motif collection with more than 30,000 motifs. We benchmarked SCENIC+ on diverse datasets from different species, including human peripheral blood mononuclear cells, ENCODE cell lines, melanoma cell states and Drosophila retinal development. Next, we exploit SCENIC+ predictions to study conserved TFs, enhancers and GRNs between human and mouse cell types in the cerebral cortex. Finally, we use SCENIC+ to study the dynamics of gene regulation along differentiation trajectories and the effect of TF perturbations on cell state. SCENIC+ is available at scenicplus.readthedocs.io ., (© 2023. The Author(s).)

Wound response programs are often activated during neoplastic growth in tumors. In both wound repair and tumor growth, cells respond to acute stress and balance the activation of multiple programs, including apoptosis, proliferation, and cell migration. Central to those responses are the activation of the JNK/MAPK and JAK/STAT signaling pathways. Yet, to what extent these signaling cascades interact at the cis -regulatory level and how they orchestrate different regulatory and phenotypic responses is still unclear. Here, we aim to characterize the regulatory states that emerge and cooperate in the wound response, using the Drosophila melanogaster wing disc as a model system, and compare these with cancer cell states induced by ras V12 scrib -/- in the eye disc. We used single-cell multiome profiling to derive enhancer gene regulatory networks (eGRNs) by integrating chromatin accessibility and gene expression signals. We identify a 'proliferative' eGRN, active in the majority of wounded cells and controlled by AP-1 and STAT. In a smaller, but distinct population of wound cells, a 'senescent' eGRN is activated and driven by C/EBP-like transcription factors (Irbp18, Xrp1, Slow border, and Vrille) and Scalloped. These two eGRN signatures are found to be active in tumor cells at both gene expression and chromatin accessibility levels. Our single-cell multiome and eGRNs resource offers an in-depth characterization of the senescence markers, together with a new perspective on the shared gene regulatory programs acting during wound response and oncogenesis., Competing Interests: SF, RB, DS, VC, CB, SD, GH, MD, XQ, DK, MA, GH, MU, AC, SA No competing interests declared, (© 2023, Floc'hlay et al.)

Octopuses are mollusks that have evolved intricate neural systems comparable with vertebrates in terms of cell number, complexity and size. The brain cell types that control their sophisticated behavioral repertoire are still unknown. Here, we profile the cell diversity of the paralarval Octopus vulgaris brain to build a cell type atlas that comprises mostly neural cells, but also multiple glial subtypes, endothelial cells and fibroblasts. We spatially map cell types to the vertical, subesophageal and optic lobes. Investigation of cell type conservation reveals a shared gene signature between glial cells of mouse, fly and octopus. Genes related to learning and memory are enriched in vertical lobe cells, which show molecular similarities with Kenyon cells in Drosophila. We construct a cell type taxonomy revealing transcriptionally related cell types, which tend to appear in the same brain region. Together, our data sheds light on cell type diversity and evolution in the octopus brain., (© 2022. The Author(s).)