Philadelphia University

Purpose To evaluate the feasibility of a transformer structure for fusing longitudinal multimodal radiomic features from chest radiographs (CXRs) and CT images to predict outcomes and identify associated clinical events in patients with COVID-19. Materials and Methods This retrospective study analyzed de-identified longitudinal CXRs and CT images in patients with polymerase chain reaction-confirmed COVID-19. Proprietary patient data (site 1) were collected between July 2020 and May 2021, and open-access patient data (obtained before February 1, 2020) were collected from site 2. Clinical outcomes included mortality, intensive care unit admission, and ventilator use during any follow-up visit. Radiomic features were extracted from lung regions in CXRs and CT images using the Cancer Imaging Phenomics Toolkit and integrated using a transformer-based model. Patient data were partitioned into training, validation, and test sets (ratio, 65:15:20). Subgroup analyses were performed across sex, site, and modality. Model performance was assessed using area under the receiver operating characteristic curve (AUC) and weighted AUC scores, with statistical significance assessed using Student t tests. Results The study included 2274 patients (946 from site 1, 1328 from site 2; mean age, 59.84 years ± 16.84, 1171 male patients). Weighted testing AUCs for predicting outcomes were 0.86 (95% CI: 0.85, 0.86) for mortality, 0.82 (95% CI: 0.81, 0.82) for intensive care unit admission, and 0.86 (95% CI: 0.86, 0.87) for ventilator usage, outperforming models trained solely on cross-sectional data or single-modal data (P < .05). Conclusion Transformer-based fusion of longitudinal multimodal radiomic data effectively predicted clinical outcomes and events associated with COVID-19. Keywords: COVID-19, Lung, Radiomics, Multi-Head Attention, Multimodal, Longitudinal, CT, Chest Radiography Supplemental material is available for this article. © RSNA, 2026.

To investigate the association between barriers reported by cardiac arrest team members and chest compression quality during in-hospital cardiac arrest (IHCA) cardiopulmonary resuscitation (CPR) attempts. This is a mixed-methods prospective cohort study. We sent post-event debriefing surveys to cardiac arrest team members following resuscitation attempts across four hospitals from 2017 to 2022. Likert-scale ratings and qualitative analysis of free-text comments were used to categorize events as having barriers present. We investigated the association between barriers and key chest compression quality metrics measured from defibrillators. The association was further examined for three predefined barrier categories: CPR quality, teamwork and communication. We included 313 IHCAs with complete defibrillator and survey data, of which 133 (42.5%) events had barriers reported. The odds ratio (OR) of having a CCF ≥80% was 0.55 (95% CI: 0.35-0.89) when barriers were reported. IHCAs with any reported barriers had an increase in the longest pause duration of 3.21s (95% CI: -1.91 to 8.38) compared to IHCAs without reported barriers, while the OR for guideline-compliant compression rate was 1.02 (95% CI: 0.64-1.62). Communication barriers, but not teamwork and CPR quality barriers, were associated with lower odds of guideline-compliant chest compression rates (OR=0.53; 95% CI: 0.29-0.95). Barriers were frequently reported during IHCA and were associated with a significantly lower odds for a CCF ≥80% but not significantly associated with the longest pause duration and guideline-compliant chest compression rates. The category of communication barriers appeared to be the main driver of associations with chest compression quality metrics.

Type of the article: Research articleThe increasing development of digital business environments has contributed to the diversification of knowledge sources globally, making smart knowledge management crucial for enhancing the accuracy of decision-making processes. This study aims to investigate the impact of AI-driven capabilities, including adaptive learning, intelligent analytics, automation capability, integration capability on knowledge systems, and the role of smart knowledge management as a mediating factor within the context of the Federal Civil Service Council in Baghdad, Iraq. The study employed a quantitative method to collect data between April 2025 and August 2025 from 161 employees with at least three years of experience in knowledge management, organizational content and records, data, and machine learning. This sample included knowledge management managers, knowledge management specialists, data analysts, knowledge support technicians, and operations managers at the Federal Civil Service Council. The findings indicate that enhancing AI-driven capabilities across the four dimensions of adaptive learning, intelligent analytics, automation capability, and integration capability contributes to organizational success. This is evident from the correlation between adaptive learning (p = 0.012, &amp;amp;lt; 0.279), analytical intelligence (p = 0.018, &amp;amp;lt; 0.213), automation capabilities (p = 0.02, &amp;amp;lt; 0.05), and knowledge systems. The study found that intelligent knowledge management plays a crucial mediating role in the relationship between AI capabilities and knowledge systems, contributing to the success of digital organizations and the accuracy of decision-making. This is further demonstrated by the positive correlation between the dimensions of AI capabilities and knowledge systems.&amp;amp;nbsp;

Colorectal cancer (CRC) is the second-leading cause of cancer-related deaths. Mutations in the tumor-suppressor APC initiate CRC in part by preventing the glycogen synthase kinase 3 (GSK3) kinase from phosphorylating β-CATENIN, leading to its stabilization and transactivation of mitogenic target genes. While the importance of β-CATENIN phosphorylation by GSK3 is well established, APC regulation of GSK3 activity upon other targets is not understood. Here, we identify the H4K20 methyltransferase SETD8 as a target of APC-coordinated GSK3 phosphorylation in the intestinal epithelium. We find that phosphorylation by GSK3 restrains the oncogenic activity of SETD8, with loss of phosphorylation sensitizing mice to oncogenic insults. Mechanistically, loss of SETD8 phosphorylation in tumors results in a loss of H4K20 monomethylation (H4K20me1) deposition at oncogenic cholesterol biosynthesis and fetal intestinal genes, allowing for their activation in part through gain of YAP accessibility. These results underscore the importance of SETD8 in CRC and represent a novel β-CATENIN-independent oncogenic consequence of APC loss.

Abstract Human rights law ensures both nondiscrimination and substantive rights. These two types of protection are conceptually distinct. But they are often intertwined in practice, because persons with vulnerable identities are especially at risk of being deprived of substantive rights. So how should human rights laws and institutions handle situations at the interplay of nondiscrimination and substantive rights? There is no single answer. Instead, as this article describes, three different methods are employed in practice. In some contexts, human rights actors take a disaggregated approach, looking separately at nondiscrimination and substantive rights. At other times, human rights law itself spells out a specific substantive rule—a specified approach—to protect a particularly vulnerable group, such as requiring paid leave for working mothers after childbirth. Yet a third method is a holistic approach that highlights linkages between substantive rights and nondiscrimination. This article discusses each of these approaches and identifies trade-offs inherent in each approach. It then goes on to show, through a case study of several International Covenant on Civil and Political Rights articles, how all three of these approaches can be found and applied within a single human rights instrument. The article concludes with some suggestions for how to pick between the three approaches in different contexts within and beyond human rights law.

Determine if preterm infants have prolonged therapeutic post-discontinuation antibiotic exposures (PDAE) following empiric ampicillin. Prospective study of 27 infants ≤7 days and <37 weeks gestational age (GA) receiving ampicillin (200 mg/kg/day); 49 post-discontinuation PK samples were collected. Exposures were predicted using PK simulations and a prior ampicillin PK model. The probability of target attainment 24- and 36-h after the final ampicillin dose for various minimum inhibitory concentrations (MICs) and the duration of therapeutic PDAE was calculated. At 24- and 36-h after ampicillin, the probability of exposures ≥1 μg/mL was 95% and 60%, respectively. PDAE (≥1 μg/mL) lasted a median 33 h (95% confidence interval: 15, 79), and varied with GA, from median 53 h (<28 weeks GA) to 27 h (34-36 weeks GA). Many preterm infants experience therapeutic exposures at least 24 h after the final ampicillin dose. Shorter courses could be considered.

CLN3 disease, also called Juvenile Neuronal Ceroid Lipofuscinosis (JNCL), or Batten disease, is an ultra‑rare, neurodegenerative lysosomal storage disorder generally affecting individuals during the first decade of life. There can be a delay in diagnosis or misdiagnosis due to a lack of awareness, and when the most common presenting symptom of visual loss is attributed to more common conditions affecting vision. We used a previously published Expert Mapping Tool (EMT) to identify multidisciplinary professionals with diagnostic or clinical management expertise, as well as patient advocates with experience of CLN3 disease. A systematic literature review of published evidence using the Preferred Reporting Items for Systematic Reviews and Meta‑Analyses (PRISMA) guidance was conducted independently and simultaneously to develop key clinical care statements. Each statement was based on the strength of the evidence. The statements formed the basis of an international modified-Delphi consensus process using a virtual meeting platform (Within3). Experts were asked to agree or disagree with each statement and suggest any changes. Statements that reached a consensus of 75% or over are the guiding statements within this manuscript. The processes and manuscript have been independently assessed using the Appraisal of Guidelines for Research and Evaluation (AGREE II) criteria. Thirty‑nine international experts from eight specialities were identified, including a patient advocate. Fifty‑three recommendation statements were developed covering eleven domains: General statements, Diagnostics, Clinical Recommendations and Management, Assessments, Social Considerations, Ocular Management, Epilepsy/Seizures, Nutrition, Respiratory Health, Sleep and Rest, and End-of-Life Care. Consensus was reached after one round of voting for all except three statements. The overall AGREE II score for developing these recommendations was 6.4, where 1 represents the lowest and 7 is the highest quality. Currently, there are no comprehensive clinical recommendations for CLN3 disease. These recommendations provide a comprehensive, evidence- and consensus‑based tool that can be used by all healthcare professionals involved in the management of CLN3 disease and other similar neurodegenerative conditions. The goal is to address the unmet clinical need for CLN3 disease management and complement other information available.