Thomas Rimmele

Background: Human error is a leading cause of preventable harm in clinical care, driven by factors such as cognitive overload and staff turnover. While customisable digital cognitive aids (cDCAs) have emerged as real-time protocol-tailored support, a framework to quantify their total impact on human error and its fundamental limits has been lacking. Methods: We conducted a pooled analysis of five randomised high-fidelity simulation trials with consistent methodologies, including 370 healthcare professionals across diverse clinical settings and levels of experience. Using bootstrap resampling, we modelled the distributions of technical and non-technical skills (TS and NTS) to quantify the impact of cDCAs on clinical competence and on Total Human Error (THE)—defined as the sum of systematic deviation from standards (bias ² ) and inter-individual variability (variance). Findings: The use of cDCAs reduced THE by 75% in a novice user context. This effect was driven by concurrent, drastic reductions in systematic deviation from standards ( bias ² : 328.1 vs 1377.1) and inter-individual variability ( variance : 124.3 vs 210.0). This was reflected in significant improvements in both technical (81.9±0.8 vs 62.9±1.0, presidual error threshold , quantifying an empirical upper bound of ∼25% for what we define as Irreducible Human Error (IHE). Interpretation: By reducing both systematic bias and performance variability, cDCAs demonstrably harmonise clinical practices and enhance competence robustness. Our analysis provides the first empirical framework to quantify this beneficial effect, revealing in turn a ∼25% residual error that delineates the fundamental limits of performance enhancement achievable via procedural workflow support. We posit this threshold serves as an empirical upper bound for Irreducible Human Error (IHE)—errors arising not from procedural flaws but from higher-order cognitive or interpersonal factors. Establishing IHE as a new benchmark for patient safety thus provides foundational evidence for a model of augmented practice, where complementary innovations such as AI may be required to move beyond procedural support, augment clinical judgement, and uphold human-centred care. Research in Context: Evidence before this study: Cognitive support has long been used to mitigate human error in high-stakes environments. ‘Traditional’ cognitive support tools (e.g., paper checklists) improve adherence to technical protocols during medical crises, but their impact on non-technical skills—such as communication and decision-making—is limited and their clinical adoption remains low. Early digital aids largely replicated these static tools, often lacking the ergonomic integration needed for real-time clinical use and failing to leverage the full potential of digital platforms. Consequently, no prior study had systematically assessed the impact of customisable digital cognitive aids (cDCAs) on both technical and non-technical skills across diverse clinical domains to establish their overall efficiency and robustness . Furthermore, no prior study has established a comprehensive framework for evaluating their effects on ‘Total Human Error’ (THE)—encompassing both bias and variability in practice—or introduced a measurable threshold for an ‘Irreducible Human Error’ (IHE) in clinical care. What this study adds: This study is the first to quantify competence—defined as the integration of procedural proficiency (TS) and cognitive-behavioural dimensions (NTS)—and measured the impact of cDCAs on TS and NTS performance and variability, across multiple clinical settings and experience levels. We pooled five randomised controlled trials with consistent methodologies and used a resampling technique (bootstrap analysis), which allowed us to model distributions of performance and assess robustness across diverse professional backgrounds. Unlike traditional digital checklists, which often impose cognitive effort or disrupt team workflows, cDCAs are adaptive interfaces, integrating seamlessly into decision-making with minimal cognitive load. Our work systematically quantifies clinical competence and THE across both TS and NTS. We demonstrated that cDCAs significantly reduced systematic bias—defined as deviation from expected standards—along with inter-individual and inter-situation variability, thereby harmonising clinical practices and improving reliability—even in high-stakes scenarios. The reduction in inter-situation variability is particularly relevant, as it strengthens the robustness of clinical care delivery, ensuring consistent performance across diverse settings. By defining and quantifying IHE, we establish a benchmark for understanding the limits of human performance—beyond which cognitive aids alone may be insufficient. Implications of all the available evidence: Integrating customisable, ergonomically optimised cDCAs into routine clinical workflows provides a scalable solution to reduce THE by harmonising practices and improving adherence to care standards. This is particularly valuable in resource-limited settings, where cDCAs could help exchange expertise. By establishing IHE as a measurable threshold, this study provides a foundation for further innovations in cognitive support. While current cDCAs provide substantial reductions in THE, these findings raise the question of whether AI could further complement cognitive aids while preserving human expertise at the core of decision-making. Future research should explore how AI-enhanced cognitive aids might ethically and transparently address residual human error, ensuring these technologies reinforce—rather than undermine—the foundational principles of trust, accountability, and patient-centred care. Finally, beyond individual performance, cDCAs may contribute to global equity by promoting robust, harmonised care and enhancing knowledge retention and application across healthcare systems. In an interconnected world, where no system operates in isolation, ensuring safe, high-quality care on a global scale is imperative.

Resolving fine structures in the Sun’s corona may provide key insights into rapid eruptions and the heating of the corona. Adaptive optics systems have been used for over two decades to reach the diffraction limit of large telescopes, thereby compensating for atmospheric image blur. Current systems, however, are still limited to observations of the solar disk and fail with coronal objects, leaving fundamental coronal dynamics hidden in that blur. Here we present observations with coronal adaptive optics reaching the diffraction limit of a 1.6-m telescope to reveal very fine coronal details. Furthermore, we discovered a short-lived, fast-moving, finely twisted feature occurring during the decay phase of a flare that quickly destabilized. Coronal adaptive optics increased the spatial resolution by an order of magnitude at visible wavelengths. We report here a large portion of off-limb coronal rain material with observed scales below 100 km. This new adaptive optics scheme opens opportunities for observational discoveries at small scales beyond the solar limb in the highly dynamic corona by exploiting the diffraction limit of large ground-based telescopes.

Striated granular edges observed in the solar photosphere represent one of the smallest-scale phenomena on the Sun. They arise from the interaction of strongly coupled hydrodynamic, magnetic, and radiative properties of the plasma. In particular, modulations in the photospheric magnetic field strength cause variations in density and opacity along the line of sight, leading to their formation. Therefore, the striation patterns can be used as valuable diagnostics for studying the finest-scale structure of the photospheric magnetic field. The Daniel K. Inouye Solar Telescope allows observations of the solar atmosphere with a spatial resolution of better than 0."03 with its current instrumentation. We analyze images acquired with the Visible Broadband Imager using the G-band channel to investigate the characteristics of fine-scale striations in the photosphere and compare them with state-of-the-art radiation-MHD simulations at similar spatial resolution. Both observed and synthetic images reveal photospheric striae with widths of approximately 20$-$50 km, suggesting that at least 4-meter class solar telescopes are necessary to resolve this ultrafine structure. Analysis of the numerical simulations confirms that the striation observed in the filtergrams is associated with spatial variations in photospheric magnetic flux concentrations, which cause shifts in the geometrical height where the emergent intensity forms. Some fine-scale striation in the synthetic images originate from magnetic field variations of approximately a hundred Gauss, resulting in a Wilson depressions as narrow as 10 km. This suggests that DKIST G-band images can trace footprints of magnetic field variations and Wilson depressions at a similar scale.

1 Recently, immune function assessment has gained prominence in clinical settings. Immune functional assays (IFAs), involving in vitro stimulation, offer a relevant approach to complement traditional immunomonitoring methods which, while widely used, do not fully capture functional immune capabilities. Despite growing interest in IFAs, their added value remains unclear. To address this gap, our study aimed to determine if insights from IFAs could be replicated with unstimulated immunoprofiling. Using the same analytical pipeline, we compared transcriptomic profiles (Nanostring®) between stimulated (TruCulture®) and unstimulated (PaxGene™) samples from i) patients with an overstimulated immune system 3-4 days post-sepsis onset, and ii) patients undergoing immune reconstitution 6-months post-allogeneic hematopoietic stem cell transplantation (allo-HSCT). In sepsis, post-stimulation transcriptomic profiles revealed immune clusters linked to disease severity and outcomes, surpassing traditional markers like mHLA-DR, while baseline analyses failed to generate clinically relevant stratification. Similarly, allo-HSCT patients’ post-stimulation data revealed immune heterogeneity and treatment-related alterations not detected using baseline transcriptomic or cellular profiles alone. Our findings emphasize the value of IFAs in uncovering functional immune alterations that unstimulated assessments may miss, which could offer deeper insights into immune dysfunction. This study supports IFAs as complementary tools to current clinical practices, enhancing patient management with a functional view of immune system dynamics.

We report commissioning observations of the Si x 1430 nm solar coronal line observed coronagraphically with the Cryogenic Near-Infrared Spectropolarimeter at the National Science Foundation’s Daniel K. Inouye Solar Telescope. These are the first known spatially resolved observations of this spectral line, which has strong potential as a coronal magnetic field diagnostic. The observations target a complex active region located on the solar northeast limb on 2022 March 4. We present a first analysis of these data that extracts the spectral line properties through a careful treatment of the variable atmospheric transmission that is known to impact this spectral window. Rastered images are created and compared with extreme-UV observations from the Solar Dynamics Observatory (SDO) Atmospheric Imaging Assembly (AIA) instrument. A method for estimating the electron density from the Si x observations is then demonstrated that makes use of the forbidden line density-sensitive emissivity and an emission-measure analysis of the SDO/AIA bandpass observations. In addition, we derive an effective temperature and nonthermal line width across the region. This study informs the calibration approaches required for more routine observations of this promising diagnostic line.

The strongly coupled hydrodynamic, magnetic, and radiation properties of the plasma in the solar chromosphere make it a region of the Sun's atmosphere that is poorly understood. We use data obtained with the high-resolution Visible Broadband Imager (VBI) equipped with an Hβ filter and the Visible Spectro-Polarimeter (ViSP) on the Daniel K. Inouye Solar Telescope to investigate the fine-scale structure of the plage chromosphere. To aid in the interpretation of the VBI imaging data, we also analyze spectra from the CHROMospheric Imaging Spectrometer on the Swedish Solar Telescope. The analysis of spectral properties, such as enhanced line widths and line depths, explains the high contrast of the fibrils relative to the background atmosphere demonstrating that Hβ is an excellent diagnostic for the enigmatic fine-scale structure of the chromosphere. A correlation between the parameters of the Hβ line indicates that opacity broadening created by overdense fibrils could be the main reason for the spectral line broadening frequently observed in chromospheric fine-scale structures. Spectropolarimetric inversions of the ViSP data in the Ca ii 8542 Å and Fe i 6301/6302 Å lines are used to construct semiempirical models of the plage atmosphere. Inversion outputs indicate the existence of dense fibrils in the Ca ii 8542 Å line. The analyses of the ViSP data show that the morphological characteristics, such as orientation, inclination, and length of fibrils, are defined by the topology of the magnetic field in the photosphere. Chromospheric maps reveal a prominent magnetic canopy in the area where fibrils are directed toward the observer.

We report commissioning observations of the Si X 1430 nm solar coronal line observed coronagraphically with the Cryogenic Near-Infrared Spectropolarimeter (Cryo-NIRSP) at the National Science Foundation's Daniel K. Inouye Solar Telescope (DKIST). These are the first known spatially resolved observations of this spectral line, which has strong potential as a coronal magnetic field diagnostic. The observations target a complex active region located on the solar northeast limb on 4 March 2022. We present a first analysis of this data, which extracts the spectral line properties through a careful treatment of the variable atmospheric transmission that is known to impact this spectral window. Rastered images are created and compared with EUV observations from the SDO/AIA instrument. A method for estimating the electron density from the Si X observations is then demonstrated that makes use of the forbidden line's density-sensitive emissivity and an emission-measure analysis of the SDO/AIA bandpass observations. In addition, we derive an effective temperature and non-thermal line width across the region. This study informs the calibration approaches required for more routine observations of this promising diagnostic line.

The Cryogenic Near-Infrared Spectropolarimeter (Cryo-NIRSP) is now conducting science operations at the National Science Foundation’s Daniel K. Inouye Solar Telescope (DKIST). We report results obtained during instrument commissioning that advance multiwavelength coronagraphic observations in the infrared. This includes the first observations of the Fe xiii 1075 nm, Fe xiii 1079 nm, Si x 1430 nm, and Si ix 3934 nm forbidden lines. The Si ix observations, in particular, significantly improve upon the few previous ground-based detections and open up this diagnostic for more routine study. We analyse long-slit spectra in each line sampling elongations from 1.06 to 1.52 solar radii above the northeast solar limb on 2022 February 14. Line characteristics as a function of radial distance are derived and discussed in comparison to modeled emission emergent from global coronal magnetohydrodynamic models with different heating prescriptions. We find favorable correspondence between the observations and different aspects of these models, and further demonstrate the utility of infrared observations for constraining coronal models. Continued DKIST/Cryo-NIRSP observations including polarimetric data, together with ongoing improvements in data calibrations, promise significant value for coronal studies.

The Daniel K. Inouye Solar Telescope (DKIST) is a ground-based observatory for observations of the solar atmosphere featuring an unprecedented entrance aperture of four meters. To address its demanding scientific goals, DKIST features innovative and state-of-the-art instrument subsystems that are fully integrated with the facility and designed to be capable of operating mostly simultaneously. An important component of DKIST’s first-light instrument suite is the Visible Broadband Imager (VBI). The VBI is an imaging instrument that aims to acquire images of the solar photosphere and chromosphere with high spatial resolution and high temporal cadence to investigate the to-date smallest detectable features and their dynamics in the solar atmosphere. VBI observations of unprecedented spatial resolution ultimately will be able to inform modern numerical models and thereby allow new insights into the physics of the plasma motion at the smallest scales measurable by DKIST. The VBI was designed to deliver images at various wavelengths and at the diffraction limit of DKIST. The diffraction limit is achieved by using adaptive optics in conjunction with post-facto image-reconstruction techniques to remove residual effects of the terrestrial atmosphere. The first images of the VBI demonstrate that DKIST’s optical system enables diffraction-limited imaging across a large field of view of various layers in the solar atmosphere. These images allow a first glimpse at the exciting scientific discoveries that will be possible with DKIST’s VBI.