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Psychometric Properties of Pain Scales in Inpatient Settings: An Umbrella Review
No full textAims: To identify the pain assessment scales with the best psychometric properties to be used by nurses in an inpatient setting. Design: Umbrella review. Methods: A comprehensive search of four databases was conducted for systematic reviews published from July 2013 to November 2024, focusing on psychometric properties of pain scales used in inpatient settings. Inclusion criteria required scales to assess subjective or behavioural pain and be nurse-administered, while reviews without detailed psychometric data were excluded. Screening, quality appraisal (JBI checklist), and data extraction were performed independently by two researchers. Data synthesis combined qualitative and quantitative approaches, with psychometric properties evaluated using the COSMIN checklist. The study was reported in accordance with the Preferred Reporting Items for Overviews of Reviews (PRIOR) statement. Results: Seventeen articles met the inclusion criteria, identifying 41 scales used across various patient populations, including critical care, paediatric, postoperative, cancer, cerebral palsy, disorders of consciousness, low back and neck pain, stroke and verbal communication disorders. The Paediatric Pain Profile, the Breakthrough Pain Assessment Tool and the Questionnaire on Pain caused by Spasticity demonstrated adequate psychometric properties, although the positive findings for the latter two should be confirmed by at least one additional study. Most of the scales (n = 36) require further studies to validate their use in clinical practice. For two scales, their clinical use remains questionable. Conclusion: The Paediatric Pain Profile, the Breakthrough Pain Assessment Tool, and the Questionnaire on Pain caused by Spasticity can be recommended for use. Unidimensional scales should complement, rather than replace, multidimensional scales to ensure a comprehensive pain assessment. Standardising documentation with validated scales enhances clinical decision-making, care quality, research usability, and reduces documentation burden
A Review of Prostatitis
No full textA recent Review on prostatitis provided a comprehensive summary but presented computed tomography (CT) as the sole advanced imaging technique for suspected prostatic abscess. In our view, magnetic resonance imaging (MRI) offers distinct advantages over CT in this clinical context. Transrectal ultrasonography (TRUS) is the first-line study for diagnosis of prostatic abscess, with sensitivity approaching 80%, and provides the added benefit of enabling image-guided drainage. Its limitations include operator dependency, patient discomfort, and inability to reliably assess extraprostatic spread of infection. For patients unable to undergo TRUS, CT is widely used because it is an easily accessible and cost-effective alternative. Computed tomography effectively visualizes larger abscesses and gas-forming infections but is less sensitive for small or multiloculated abscesses. For patients who are hemodynamically unstable, CT is useful because it can be rapidly obtained and iswidely available.However, the rationale for CT use does not apply to subacute or chronic presentations of prostatitis, for which MRI can have improved diagnostic accuracy. Magnetic resonance imaging provides superior soft tissue contrast, allowing earlier and more accurate identification of abscesses, which appear T1-hypointense and T2-hyperintense with restricted diffusion and peripheral enhancement. Diffusion-weighted imaging further enhances abscess detection and characterization, with very low diffusion coefficient values reflecting pus content. Magnetic resonance imaging also is helpful in defining extraprostatic extension of infection to seminal vesicles, periprostatic tissues, or pelvic sidewalls. In addition, MRI does not use ionizing radiation, an important consideration in younger or middle-aged men who require follow-up imaging because CT radiation increases oncologic risk andmay impair spermatogenesis, potentially affecting fertility. With an external phased-array coil, high-quality images can be obtained without an endorectal probe, improving tolerability in symptomatic patients
Conformal Predictive Monitoring for Multi-modal Scenarios
No full textWe consider the problem of quantitative predictive monitoring (QPM) of stochastic systems, i.e., predicting at runtime the degree of satisfaction of a desired temporal logic property from the current state of the system. Since computational efficiency is key to enable timely intervention against predicted violations, several state-of-the-art QPM approaches rely on fast machine-learning surrogates to provide prediction intervals for the satisfaction values, using conformal inference to offer statistical guarantees. However, these QPM methods suffer when the monitored agent exhibits multi-modal dynamics, whereby certain modes may yield high satisfaction values while others critically violate the property. Existing QPM methods are mode-agnostic and so would yield overly conservative and uninformative intervals that lack meaningful mode-specific satisfaction information. To address this problem, we present GenQPM, a method that leverages deep generative models, specifically score-based diffusion models, to reliably approximate the probabilistic and multi-modal system dynamics without requiring explicit model access. GenQPM employs a mode classifier to partition the predicted trajectories by dynamical mode. For each mode, we then apply conformal inference to produce statistically valid, mode-specific prediction intervals. We demonstrate the effectiveness of GenQPM on a benchmark of agent navigation and autonomous driving tasks, resulting in prediction intervals that are significantly more informative (less conservative) than mode-agnostic baselines
Long-term outcomes of superselective transcatheter embolization in high-flow priapism
No full textThis retrospective cohort study aims to evaluate the long-term outcomes of superselective transcatheter arterial embolization in patients with high-flow priapism. All patients treated with arterial embolization at our center between 2002 and 2017 for high-flow priapism were included. Demographic and clinical data were collected and analyzed. In July 2022, patients were reassessed using specific questions about their satisfaction with the treatment. Erectile function was evaluated using the International Index of Erectile Function-5 (IIEF-5) and the Erection Hardness Score (EHS). Thirteen men, with a median age of 30 years (IQR: 24-37), were included in the study. Superselective arterial embolization using permanent occlusive agents was performed in all cases. The blood flow in the fistula was interrupted leading to complete penile detumescence in all patients. At a median follow-up of 175 months (IQR: 74-197), the median IIEF-5 score was 24 (IQR: 21-25) and the median EHS was 4 (IQR: 3-4), indicating preserved erectile function. Additionally, 92.3% of patients expressed satisfaction with the treatment. Superselective transcatheter arterial embolization with non-absorbable agents demonstrates effectiveness and durability as a treatment for high-flow priapism, with preserved erectile function observed over a follow-up period exceeding 10 years. Nonetheless, the interpretation of these findings is limited by the study's small sample size and retrospective design
Unraveling Novel Genetic Determinants of Thiopurine Response Via TWAS
Full text linkAcute lymphoblastic leukemia (ALL) is the most common childhood cancer. Thiopurines such as 6-mercaptopurine (6MP) are essential in ALL maintenance therapy. However, dose-limiting toxicities can significantly disrupt treatment. While genetic variants in TPMT and NUDT15 are known to affect thiopurine response, many patients with normal function genotypes in these genes still experience adverse effects, suggesting that additional genes might be involved. We analyzed 663 pediatric ALL patients enrolled in the AALL03N1 trial to identify novel genetic determinants of 6MP sensitivity, focusing on individuals with normal function TPMT and NUDT15 genotypes. A transcriptome-wide association study (TWAS) was conducted to focus on expression quantitative trait loci (eQTLs). Findings were validated in two independent cohorts: St. Jude Total Therapy XV (n = 390) and XVI (n = 552). TWAS identified 31 genes associated with 6MP dose intensity (q-value < 0.90). Of these, the imputed GNAQ expression was positively correlated with 6MP dose intensity and passed multiple testing thresholds in the validation cohorts. The rs60561071 variant, the eQTL in the GNAQ TWAS model, was associated with reduced gene expression and lower 6MP dose intensity. This study identifies GNAQ as a novel gene associated with thiopurine tolerance in ALL patients lacking known risk alleles in TPMT and NUDT15. Moreover, this research highlighted the innovative use of TWAS, providing deeper insights into the molecular mechanisms that explain drug response variability
Simultaneous probe of the charm and bottom quark Yukawa couplings using t t-bar H events
No full textGold nanoparticles decorated with fluorinated poly(ethylene oxide): structural and functional insights
No full textFluorinated hybrid organic–inorganic nanomaterials have attracted interest for applications ranging from biomedicine to superhydrophobic surfaces. However, few examples of fluorinated hybrid nanoparticles (F-NPs) establish a clear relationship between the structure of the fluorinated component and the properties of the hybrid system. This gap limits understanding of structure–property correlations and hinders the development of F-NPs with tailored functionalities. Here, we report the design, synthesis, and characterization of gold NPs passivated with fluorinated thiolates (F-NP2), combining high fluorine content with excellent dispersibility in both organic and aqueous solvents. The gold core measures approximately 2 nm, while the hydrodynamic diameter is around 12 nm, consistent with SAXS data. Electron Spin Resonance (ESR) studies reveal an exceptionally strong interaction between a hydrophobic radical probe and the NP coating, surpassing previously reported systems and indicating a high capacity for hosting hydrophobic, drug-like molecules. Molecular dynamics simulations support this behavior, showing a highly folded fluorinated segment and limited shielding by the polar mPEG550 end, which also explains reversible aggregation at high NP concentrations observed via dynamic light scattering. Finally, preliminary 19F MRI data acquired at 7 T demonstrate a good signal-to-noise ratio, suggesting that these F-NPs may serve as sensitive fluorine-based tracking agents for biomedical applications
Extending Decision Predicate Graphs for Comprehensive Explanation of Isolation Forest
No full textThe need to explain predictive models is well-established in modern machine learning. However, beyond model interpretability, understanding pre-processing methods is equally essential. Understanding how data modifications impact model performance improvements and potential biases and promoting a reliable pipeline is mandatory for developing robust machine learning solutions. Isolation Forest (iForest) is a widely used technique for outlier detection that performs well. Its effectiveness increases with the number of tree-based learners. However, this also complicates the explanation of outlier selection and the decision boundaries for inliers. This research introduces a novel Explainable AI (XAI) method, tackling the problem of global explainability. In detail, it aims to offer a global explanation for outlier detection to address its opaque nature. Our approach is based on the Decision Predicate Graph (DPG), which clarifies the logic of ensemble methods and provides both insights and a graph-based metric to explain how samples are identified as outliers using the proposed Inlier-Outlier Propagation Score (IOP-Score). Our proposal enhances iForest’s explainability and provides a comprehensive view of the decision-making process, detailing which features contribute to outlier identification and how the model utilizes them. This method advances the state-of-the-art by providing insights into decision boundaries and a comprehensive view of holistic feature usage in outlier identification.—thus promoting a fully explainable machine learning pipeline
MDO Optimization of a Supersonic Aircraft by Reduced Order Models
No full textIn this paper a Fighter Supersonic Jet model is optimized to minimize RCS electromagnetic scattering and
maximize aerodynamic efficiency. To reduce the computational effort while keeping at the same time a high
level of reliability, Reduced Order Models (ROM) are defined to approximate the aerodynamic and the
electromagnetic fields of the Jet, as a function of a reduced number of modes (principal components).
The entire process of simulation automation and optimization has been integrated into the VOLTA web-
based collaboration platform. Geometrical parameters related to the shape of the wings and tail planes are
automatically updated on the CAD model, and CFD and electromagnetic simulations are executed on a
distributed computational network using a Eulerian solver and a RCS code, on given conditions of Mach
number and emitting frequency. An accurate surrogate ROM model trained on the database made by the
CFD fields and the RCS curves is then used by the MDO optimization algorithm to evaluate the performance
of the designs proposed, until the defined objectives are optimized
