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In this work, we review the history and current role of global fits in the search for physics beyond the Standard Model (BSM), including precision tests of the Standard Model (SM). Although BSM global fits were initially focused on minimal supersymmetric models, we describe how fits have evolved in response to new data from the Large Hadron Collider (LHC) and elsewhere, expanding to encompass a broad spectrum of BSM scenarios including non-minimal supersymmetry, axion-like particles, extended Higgs sectors, dark matter models, and effective field theories such as SMEFT. We discuss how the role of global fits has shifted from forecasting possible signals of new physics at the LHC to understanding the impact of null results from LHC run-I and II and the discovery of the Higgs boson, and how interest has shifted from global fits for parameter estimation to comprehensive model comparison. We close by discussing potential trends and future applications, emphasizing the potential for machine learning and artificial intelligence to enhance the efficiency of sampling algorithms and comparison between theory and experiment, as well as collaboration and software development.
Sustainable groundwater management remains a critical challenge in semi-arid regions, where climatic variability and increasing anthropogenic pressures constrain aquifer resilience. In this context, the present study applies an Analytical Hierarchy Process (AHP)-based GIS framework to delineate groundwater potential zones in the Bouanane Basin, a data-scarce semi-arid environment. The analysis integrates nine hydro-environmental factors, including precipitation, land use, lineament density, drainage density, geology, soil type, slope, elevation, and NDVI, to capture both structural and surface controls on groundwater occurrence. The AHP weighting scheme achieved an acceptable level of consistency (CR = 0.070), ensuring the reliability of the pairwise comparison process. he results identify three groundwater potential classes: very low (1.24%), low (84.88%), and moderate (13.87%). Model performance was evaluated using data from 27 wells and validated through the kappa coefficient (κ = 0.82), indicating strong agreement between predicted and observed conditions. The findings highlight the dominant influence of geological structure, lineament density, and precipitation in controlling groundwater distribution. The predominance of low to moderate potential zones reflects the hydro-climatic and geological constraints typical of semi-arid environments. This study provides a spatially explicit assessment of groundwater potential and contributing factors, offering a practical basis for groundwater management in data-limited semi-arid basins.
The visual pathway is an important model system for remyelination and neuroprotection trials in multiple sclerosis, due to its accessibility and the availability of validated methods including visual evoked potential and optical coherence tomography. However, visual evoked potentials are sometimes undetectable and demonstrate limited reliability after acute optic neuritis. This study aims to investigate novel magnetoencephalography markers for assessing myelin content and neuronal dysfunction in the early phase of optic neuritis and describes their inter-run reproducibility ('over a single visit') and association with short-term visual outcomes. Patients with unilateral acute optic neuritis were recruited and underwent ophthalmological assessments, brain MRI and magnetoencephalography. Magnetoencephalography data were acquired during visual stimulation with an alternating checkerboard pattern. We used source localization to reconstruct brain activity in the primary visual cortex (V1) and analysed it in the temporal and frequency domains. In the temporal domain, we focused on M100 latency-the magnetic counterpart of P100 latency. In the frequency domain, we assessed the spectral richness of the steady-state evoked field response by harmonic count, which reflects the diversity of frequency components present in the brain signal. Thirty-two patients were included at a median of 54 days [interquartile range = (37.5-78)] post-symptom onset of optic neuritis. Among patients with optic neuritis, visual evoked field recordings were detectable in 77% of cases, compared with 66% for visual evoked potential recordings. M100 latency demonstrated an excellent inter-run reproducibility for both fellow and affected eyes [intra-class correlation coefficient (ICC) >0.8, mean absolute inter-run difference of 2.99 ± 6.53 and 3.76 ± 7.53 ms, respectively]. By comparison, the reproducibility of P100 latency was good for fellow eye (ICC = 0.7, mean absolute inter-run difference of 3.9 ± 6.2 ms) but moderate for affected eye (ICC = 0.6, mean absolute inter-run difference of 9.1 ± 21.8 ms). In the frequency domain, the harmonic count correlated strongly with ganglion cell layer volume (r = 0.68, P = 0.0001), likely reflecting functional consequences of neuronal loss. Measures reflecting demyelination (P100 and M100 latencies) correlated with measures of neuronal damage (ganglion cell layer volume and harmonic count) from both conventional and magnetoencephalography assessments. Visual impairment was associated with neuronal damage (parameter estimates: β = 0.49, P = 0.017 for ganglion cell layer volume, β = 0.57, P = 0.003 for harmonic count) but not with demyelination measures. Our results highlight magnetoencephalography as a reproducible and comprehensive tool to study both myelin content and neuronal dysfunction shortly after optic neuritis and suggest that, at this early stage, neuronal damage is already the main driver of visual outcome.
Background Gastric oxyntic gland neoplasms (GOGNs)-including oxyntic gland adenoma (OGA), gastric adenocarcinoma of fundic gland type (GA-FG), and gastric adenocarcinoma of fundic gland mucosa type (GA-FGM)-are rare epithelial neoplasms that often lack overt malignant appearance on endoscopy. This study aimed to characterize the endoscopic features of GOGNs that may facilitate their recognition. Methods We retrospectively analyzed consecutive, histologically confirmed GOGNs diagnosed at a tertiary center between January 2019 and July 2025. Endoscopic features on white-light endoscopy (WLE), magnifying narrow-band imaging (NBI), and endoscopic ultrasonography (EUS) were evaluated. Results Among 156,240 upper endoscopic examinations, 35 patients were diagnosed with GOGNs (0.028%). Lesions were mostly small (median 6 mm) and located in the fundus/upper body (52%), predominantly Paris type 0-IIa (57%) or subepithelial-like elevations (60%). Color was similar to the surrounding mucosa (49%) or mildly reddish (37%), occasionally showing branching vessels (31%) or focal pigmentation (14%). On NBI, OGA and GA-FG lesions ( n = 12) frequently showed regularly enlarged crypt openings (92%) and branching vessels (83%) with ill-defined margins (75%), whereas GA-FGM ( n = 4) more often showed a distinct demarcation line (75%) with irregular microvascular/microsurface patterns (50%). EUS demonstrated localization mainly within the middle-to-deep mucosal layer and occasional submucosal extension, with intact muscularis propria. Conclusions GOGNs typically present as small, inconspicuous elevated lesions in the fundus or upper stomach, often with near-normal or slightly reddish mucosal color and characteristic surface vascular and magnifying features. Awareness of these endoscopic patterns may improve recognition of GOGNs during routine endoscopy. Larger studies are needed to validate these findings.
To compare differences in risk factors and 90-day mortality prediction from 2 machine learning (ML) models with a previously published non-ML model and investigate their validity in an external cohort. Prospectively collected data from 2 separate randomized controlled trial (RCT) cohorts from 2020 to 2021, the Therapeutics for Inpatients with COVID-19 (TICO/ACTIV-3) Trial (derivation and internal validation cohort) and the Inpatient Treatment with Anti-Coronavirus Immunoglobulin (ITAC) Trial (external validation cohort) were used. Data were collected from 114 sites in 10 countries (TICO/ACTIV-3) and 63 sites in 11 countries (ITAC). A ML pipeline including 5 classification models, and 1 survival model was used for risk factor identification and clinical outcome prediction. Risk factors were compared between a ML-based classification model, a ML-based survival model and a previously published Cox model. Performance of the ML-based classification model was compared across TICO/ACTIV-3 and ITAC. A total of 2625 (TICO/ACTIV-3) and 579 (ITAC) adults hospitalized for COVID-19 were included. Some overlap of risk factors was identified across models. Five were identified in all models, 3 only in ML models, and 4 only in the non-ML model. The ML model showed good predictive performance in TICO/ACTIV-3. Internal validation showed no overfitting. Lower model performance was observed in ITAC (-15.8%), but performance remained above chance level. Differences in methods for risk factor identification using ML and non-ML complicates the comparison of results derived from each approach, but using multiple approaches may unveil overlooked risk factors. Risk factor identification may benefit from integrating both ML and non-ML methods, but external validation is necessary, even in RCTs.
Spondyloarthropathies (SpA) are characterized by low back pain and limited mobility. Therefore, physical activity (PA) is an essential part of the treatment, yielding positive effects on clinical symptoms. Digital health applications (DHAs) present new opportunities to promote clinical outcomes, however, their long-term effectiveness is often limited by low adherence and high dropout rates.This study investigates whether integrating personalized or AI-driven coaching enhances the therapeutic benefits of DHA in patients with SpA. SpAs patients were randomized into one of 3 groups. They were instructed to exercise at least 2-3 times per week for 6 months with the DHA according to their group (intervention groups: ViViRA (with personal coaching) or Kaia Health (with AI-based coaching); control group: ViViRA (without coaching)). Personal coaching consisted of a one-time, 30-min online coaching session prior to using DHA, while the AI coaching consisted of video-based AI integrated into DHA to provide movement guidance during each session. At baseline, after 3 and 6 months sociodemographic, questionnaires and mobility were assessed. Data from 78 participants were analyzed (mean age 51 years; 68% female). All three digital interventions showed a significant improvement in mobility (Bath Ankylosing Spondylitis Metrology Index (BASM), range: 0-10, lower scores = better mobility; BL-3 month: mean BASMI change - 0.6 to - 0.7; all p < 0.001). Pain intensity decreased substantially in all arms (PainDETECT, neuropathic pain, range: 0-38, higher scores = more severe pain; BL-6 month: mean reduction - 4.6 to - 6.6 points; all p ≤ 0.006). PAHCO (Physical Activity-related Health Competence) control competence increased over time and reached statistical significance only in the ViViRA + coaching group (PAHCO: higher scores = better physical activity-related health competence; BL-6 month: + 1.02, p = 0.013) but did not exceed the other interventions in a direct comparison. Overall, none of the coaching strategies showed significant superiority over the stand-alone digital therapy. Adherence was the same in all groups after 3 months (2-3 weekly use of DHA). Digital movement therapy with the use of DHA improves mobility and pain independently of coaching in SpAs patients. In contrast, personal coaching has been shown to improve health-related skills which could indicate potential benefits for self-management and long-term treatment adherence.Trial registration The study is registered in the German clinical trial registry (DRKS) under the following ID: DRKS00035191, https://www.drks.de/search/de/trial/DRKS00035191/details, Registration date: 01.10.2024.
Accurate measurement of the residual sac after endovascular aortic repair (EVAR) is essential for effective surveillance, guiding detection of complications and decisions regarding reintervention. While two-dimensional ultrasound (2D-US) remains standard-of-care, it is limited by operator variability. Three-dimensional ultrasound (3D-US) with modeling software has demonstrated improved precision but remains resource-intensive. The introduction of three-dimensional Software-Assisted Ultrasound (3D-SAUS) offers an automated, on-cart alternative for more streamlined clinical use. This study compares 3D-SAUS with 2D-US in measuring maximum residual sac diameter in EVAR patients, focusing on variability and clinical applicability. Patients previously treated with EVAR and following US-based follow-up were scanned by three or four experienced ultrasound operators. The maximum anterior-posterior residual sac diameter was measured for all patients using 2D-US and 3D-SAUS. Outcomes were median and limits of agreement (LoA) with 95% confidence intervals for both modalities. Fourteen EVAR-treated patients underwent 44 paired 2D-US and 3D-SAUS scans. Median maximum residual sac diameters were 50.0 mm with 2D-US and 50.3 mm with 3D-SAUS. LoA were 3.4 mm for 2D-US and 3.6 mm for 3D-SAUS, with overlapping 95% confidence intervals (2.2-4.6 mm and 2.5-4.7 mm, respectively). The difference in LoA was not statistically significant (P=0.61). Automatic technical success was achieved in 79% of the available 3D scans. 3D-SAUS demonstrated comparable residual sac diameter measurement precision and variability to expert 2D-US in post-EVAR patients. These findings support the potential of 3D-SAUS to enhance reproducibility and standardize ultrasound-based follow-up.
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Fleming and Michel convincingly argue that the water-to-land transition put evolutionary pressure on the temporal structure of conscious vision. But their interpretation of postdictive effects, which leads them to conclude that conscious vision is slow, suffers from conceptual issues and inadvertently leads them to an overly discrete and serial model of temporal consciousness.

Spatially fractionated radiation therapy (SFRT) enables delivery of high peak doses while sparing normal tissue, yet the relative contributions of peak dose, valley dose and spatial dose distribution remain unclear. This study investigates whether spatial dose organization contributes to normal tissue response beyond conventional dosimetry descriptors.
Methods:
Acute and late skin responses were evaluated in a murine hind-limb model after single-fraction irradiation with clinically pertinent Mini-GRID and planar beam configurations that allow for peak and valley dose effects to be decoupled. Longitudinal clinical scoring, histopathological evaluation and quantitative proteomic analysis were performed up to 90 days following irradiation.
Results
With the peak dose held constant, Mini-GRID irradiation resulted in reduced toxicity compared with planar irradiation delivering higher valley doses. In contrast, conditions with similar valley doses but substantially different peak doses showed comparable outcomes. These findings suggest that maximal dose alone does not act as a predictor of normal tissue response. Distinct molecular signatures associated with spatial dose heterogeneity were identified through a proteomic analysis corresponding to spatial dose heterogeneity, which was consistent with regulated tissue remodeling and resolution of inflammation.
Conclusion:
These findings suggest that spatial dose distribution contributes significantly to normal tissue response beyond peak and valley dose magnitude alone. While valley dose defines baseline tissue injury, spatial dose organization modulates repair capacity and long-term outcome. This work provides a radiobiological framework for SFRT optimization and supports the incorporation of spatial dose descriptors, beyond conventional metrics such as PVDR, into treatment design.
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Not available.
We present a tour de force of atomistic molecular dynamics simulations involving the coordinated effort of 14 research groups of the Ascona B-DNA Consortium (ABC). This initiative provides a complete characterization of the 2080 DNA hexamers embedded in 190 carefully selected 20-mer duplexes, each simulated in replicate for at least 10 microseconds in explicit solvent. The consortium generates 0.25 petabytes of data, capturing millisecond-scale ensembles at the oligomer level and dynamics up to 10-1 seconds at the base-pair level. Analysis yields a comprehensive description of sequence-dependent DNA properties, including rare events such as backbone transitions, reversible base-pair changes, and partial unfolding. Processing these atomistic ensembles reveals a hidden physical code of DNA, helping explain rules of genome composition and evolution beyond coding regions. This community effort delivers unprecedented, validated FAIR data to support coarse-grained and AI models of DNA at cellular scale.
Robotic exoskeletons are increasingly used in neurorehabilitation, yet evidence remains limited regarding their role as assistive locomotion devices within a compensatory rehabilitation framework, particularly in individuals with complete spinal cord injury. Multidimensional evaluations integrating safety, usability, and patient-reported experience are still scarce. To evaluate the Atalante self-balancing exoskeleton as an assistive locomotion device in individuals with complete paraplegia through a multidimensional analysis conducted in a controlled clinical environment. This prospective, monocentric, longitudinal study included adults with chronic complete thoracic spinal cord injury (American Spinal Injury Association Impairment Scale grade A, neurological level T6-T12). Participants underwent an intensive 6-week program comprising 60 supervised sessions of exoskeleton-assisted training including 40 m walking per session. Outcomes were assessed across three complementary dimensions: (1) safety (medical adverse events, safety-related technical incidents, near-falls); (2) techno-functional usability (donning/doffing performance, assistance levels, cumulative walking exposure); and (3) acceptability (patient-reported comfort and perceived safety using session-based visual analogue scales). Physiological responses were evaluated using exoskeleton-assisted 6-minute walk tests. Thirteen participants were enrolled; eleven completed the full protocol. One serious adverse event occurred, a tibial plateau fracture in a participant with severe osteoporosis (hip T-score - 3.8), leading to study withdrawal. No other serious medical adverse events were observed. Across 651 sessions, four near-fall events were recorded (0.61% of sessions and 0.16% per 10 m walked). Minor adverse events were transient, and no symptomatic orthostatic hypotension was reported. Oxygen consumption, walking speed, and cost of transport (p > 0.05) remained stable between mid- and end-program assessments, while perceived exertion decreased significantly (p = 0.003). Donning time decreased from 790 [475-966] s during the first session to 223 [159-259] s during the final sessions, and doffing time from 242 [152-275] s to 55 [50-69] s, with familiarization plateau points observed after 14 and 18 sessions, respectively. Harness comfort improved over time, whereas perceived safety remained globally stable, except for transient decreases following fall-prone gait events or technical disengagements. Under supervised clinical conditions, the Atalante exoskeleton demonstrated acceptable safety and feasibility as an assistive locomotion device for individuals with complete paraplegia, enabling hands-free upright indoor walking with low metabolic demand. Severe osteoporosis emerged as a critical risk factor, supporting systematic bone densitometry and cautious exclusion criteria. These findings support the integration of self-balancing exoskeletons into compensatory rehabilitation programs and justify further studies in ecological settings to assess real-world autonomy and participation outcomes. Trial registration ClinicalTrials.gov Identifier: NCT06941896 (retrospective registration).
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We agree with Levine et al. that moral judgments track outcomes that would emerge from a balanced bargaining process. But we challenge the claim that moral cognition must therefore simulate bargaining itself. Like any evolved system that exploits deep regularities without representing them, moral cognition can produce ideal contractualist judgments without mentally representing bargaining scenarios.
The Gene Damage Index (GDI) quantifies the cumulative mutational damage of protein-coding genes in the general population and helps prioritize candidate disease genes in sequencing studies. However, the original GDI is influenced by coding sequence length and does not account for gene-specific differences in variant deleteriousness. We developed GDIv2, an updated framework correcting for coding sequence length and incorporating gene-specific normalization of CADD scores to improve discrimination between disease-relevant and non-relevant genes. Four GDIv2 implementations were generated using 1000 Genomes Project and gnomAD datasets for both GRCh37 and GRCh38 genome builds. Benchmarking against the original GDI showed that all GDIv2 versions significantly improved discrimination between relevant and accessory genes, reduced erroneous exclusion of relevant genes, and increased exclusion of accessory genes. GDIv2_1kGP_37 achieved the best AUC performance and excluded 24.6% of accessory genes while retaining 96.7% of relevant genes. Compared with RVIS, LOEUF, shet, and CoNeS, GDIv2_1kGP_37 performed similarly in AUC analyses. Combining GDIv2_1kGP_37 with CoNeS and LOEUF further improved filtering, excluding 42.7% of accessory genes while removing only 2.4% of relevant genes. GDIv2 resources are freely available at https://hgidsoft.rockefeller.edu/GDI/GDIv2.html.
The European LeukemiaNet (ELN) 2022 classification categorized both t(9;11)(p21.3;q23.3) and isolated del(7q) in acute myeloid leukemia (AML) as intermediate-risk when treated with intensive chemotherapy. However, their prognostic relevance in the context of allogeneic hematopoietic cell transplantation (allo-HCT) needs further validation. This retrospective, registry-based analysis from the EBMT assessed outcomes in adults with AML who underwent allo-HCT in first complete remission between 2010 and 2022. In the first cohort, data from 141 patients with t(9;11) were analyzed, of whom 23% had additional adverse cytogenetic abnormalities (ACA), primarily complex karyotype. Most had de novo AML (72%), had received myeloablative conditioning (57%), and peripheral blood stem cells (88%). After a median follow-up of 3 years, there were no significant differences in 2-year relapse incidence (22% vs. 18.2%, p=0.85), leukemia-free survival (66% vs. 76%, p=0.42), or overall survival (72% vs. 75%, p=0.68) between patients with non-adverse t(9;11) and those with additional ACA. The second cohort included 250 patients: 84 with del(7q), 95 with monosomy 7, and 71 with del(5q), and all without additional ACA. Most had de novo AML (59%) and had received reduced-intensity conditioning (65%). After similar follow-up, survival outcomes did not differ significantly across the groups (2-year leukemia-free survival: 61% vs. 59% vs. 52% for del(7q), monosomy 7 and del(5q), respectively). In conclusion, these findings suggest that the prognostic value of t(9;11) as intermediate-risk remains consistent in the setting of allo-HCT regardless of additional ACA, whereas del(7q), even without additional ACA, confers a risk comparable to monosomy 7 and del(5q).
Chiral-substituted carbonyl compounds can be sustainably obtained via asymmetric alkene reduction catalyzed by ene-reductases from the Old Yellow Enzyme (OYE) family. Yet OYEs are seldom implemented in scale-up reactions due to low turnover numbers (TONs). Herein, we demonstrate multigram 150 g/L scale reactions with the thermostable OYE from Thermus scotoductus (0.2 wt %) for the asymmetric reduction of monoterpenes. Best results were achieved with (S)-carvone (7.5 g), affording a record TON of 123,000, with 90% isolated yield and >99% enantiomeric excess of (2R,5S)-dihydrocarvone, and an environmental E-factor of 11.6.
Fleming and Michel discuss the slowness of conscious vision and the predictions generated by an internal model of the world. However, these two points correspond to two different times. The slowness of consciousness puts the organisms in the past, whereas predictions give them a preview of the future. Given this tension between past and future representations, when is "now"?
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