Citations

Abstract Background Cone‐beam computed tomography (CBCT) is essential for image‐guided particle therapy (IGPT), providing daily patient positioning, anatomical monitoring, and treatment verification. However, conventional single‐detector CBCT suffers from poor soft‐tissue contrast, long acquisition times, and motion artifacts, reducing its effectiveness for adaptive radiotherapy workflows. Addressing these challenges requires an advanced CBCT reconstruction approach capable of enhancing image quality while reducing scan time and radiation exposure. Purpose This study introduces a Dual Detector Combined Scanning (DDCS) CBCT reconstruction algorithm to overcome conventional CBCT limitations. By integrating a dual‐source, orthogonal imaging setup, DDCS significantly reduces scanning time and imaging artifacts. A modified Parker‐weighting algorithm further improves image reconstruction accuracy, ensuring high‐fidelity visualization. The goal is to enhance adaptive radiotherapy by improving real‐time patient positioning, dose verification, and motion management. Methods A dual‐detector CBCT system was designed to acquire orthogonal projections simultaneously, reducing scan time and improving data completeness. A modified Parker‐weighting algorithm corrected angular overlap distortions, ensuring better reconstruction accuracy. The system was evaluated using numerical and physical phantom studies to assess spatial resolution, contrast‐to‐noise ratio (CNR), and artifact reduction. Additionally, a dynamic phantom simulated respiratory motion, validating motion robustness for adaptive radiotherapy. Performance was compared against single‐detector CBCT, focusing on image fidelity, noise suppression, and computational efficiency. Results DDCS‐CBCT demonstrated higher CNR, reduced motion artifacts, and improved spatial resolution, leading to more accurate anatomical visualization. The system's efficiency enables faster, more reliable patient setup in IGPT while maintaining a lower imaging dose. Conclusion The proposed DDCS‐CBCT approach significantly improves imaging accuracy, reduces scan time, and enhances real‐time volumetric guidance in IGRT/IGPT. These findings support the clinical feasibility of the DDCS system and its integration into online adaptive radiotherapy workflows.

ABSTRACTObjectivesWe describe the types of emergency department (ED) visits managed by non‐physician providers (NPPs), including physician assistants and nurse practitioners, and emergency medicine (EM) physicians, assessing shifts in care patterns over time.MethodsWe used data from the National Hospital Ambulatory Medical Care Survey collected from 2009 to 2021. We classified visits by provider type: physician only, physician with resident, physician with NPP, and NPP only. We described characteristics of visits by provider type, including patient demographics, triage urgency, imaging, length of stay, and disposition, and analyzed using Poisson regression. We described the change in type of provider seen over this study period and further analyzed by triage urgency and hospital location.ResultsOf 1.684 billion estimated ED visits from 2009 to 2021, 1.171 billion were managed by physicians without residents or NPPs (physicians only), 136.3 million by physicians with residents, 209.1 million by physicians with NPPs, and 167.4 million by NPPs only. Patients seen by physicians only were older, were triaged as having more urgent needs, had a longer ED length of stay, and were more likely to be admitted compared to those seen by NPPs only. Physician‐only visits decreased from 77% to 62%, while NPP‐only visits increased from 6% to 11%. The physician with the NPP group similarly grew from 9% to 17%. For visits assigned a triage urgency level of 2 (“emergent”), physician‐only visits decreased by 20%, physician with NPP visits increased by 13%, and NPP‐only visits increased by 3%. In metropolitan areas, physician‐only visits dropped 14%, with a 5% increase in NPP‐only visits. In non‐metropolitan areas, physician‐only visits decreased 17%, with a 9% increase in NPP‐only visits.ConclusionsThe EM workforce has shifted, with NPPs seeing a higher percentage of patients, including both lower‐ and higher‐acuity patients. This shift is particularly prominent in rural areas but is evident across all regions.

ABSTRACT Objectives To investigate the value of cytokine, chemokine, and neurofilament light chain (NfL) concentrations in predicting relapse risk, chronic epilepsy, and functional impairment in LGI1 autoimmune encephalitis (AE). Methods Cytokines/chemokines (IL‐1‐beta, IL‐2, IL‐4, IL‐5, IL‐6, IL‐8/CXCL8, IL‐10, IL‐12p70, IL‐13, IL‐17A, GM‐CSF, TNF‐alpha, IFN‐gamma, CXCL9, CXCL10, CXCL13, BAFF) and NfL concentrations were measured in CSF and paired serum from LGI1‐AE patients evaluated at Mayo Clinic (01/2015–02/2024), using a multiplex immunoassay system (ELLA, Bio‐Techne) and correlated with clinical outcomes. A laboratory‐based cohort of LGI1‐IgG‐positive patients and control cohorts, including patients with mixed non‐inflammatory disorders (MNID), Alzheimer's disease (AD), and temporal lobe epilepsy (TLE) were analyzed. Results Forty‐four patients with LGI1‐AE were included; 29 (66%) were male, with a median age of 68.5 years (range, 8–85). Median time from symptom onset to CSF sampling was eight months (IQR, 3–17); 19/42 (45%) experienced a clinical relapse and 27% developed chronic epilepsy. Serum IL‐6, serum and CSF IL‐8/CXCL8, and IL‐17A were higher in LGI1‐IgG positive patients than MNID ( p < 0.05). TLE cytokine/chemokine profiles were similar to LGI1 AE; AD patients had lower serum IL‐6 and CSF IL‐8/CXCL8 ( p = 0.04; p = 0.01), and higher serum IL‐17A and GM‐CSF ( p = 0.004; p = 0.01) than LGI1‐AE. Higher CSF IL‐6 and IL‐8/CXCL8 in LGI1‐AE associated with clinical relapse ( p < 0.05) and higher CSF NfL associated with chronic epilepsy ( p = 0.01). Conclusion Elevations in IL‐6, IL‐8/CXCL8, and IL‐17A were identified in this LGI1‐AE cohort. CSF IL‐6, IL‐8/CXCL8, and NfL levels are potential prognostic biomarkers for risk of relapse and chronic epilepsy in LGI1‐AE.

Abstract Sex differences in cancer outcome, including that of glioblastoma (GBM), are shaped by biological, hormonal, and immunological factors and impact disease progression, treatment responses, survival, and tumor microenvironment (TME) interactions. Platelets regulate the immune responses and tumor progression in many cancers, but it is not clear how they contribute to these sex-based differences by affecting the dynamics of the TME. Here, we show that GBM patients exhibit heightened platelet reactivity driven by PAR4 signaling. In murine GBM models, both pharmacological inhibition of PAR4 using BMS986120 and genetic deletion of PAR4 significantly prolong survival in females but not males. This survival advantage is estrogen dependent: it is preserved in chromosomal male-hormonal female mice within the four-core genotype model and is rescued in ovariectomized mice treated with estrogen. The survival benefit is TME specific and is mediated by platelet-driven enhancement of CD8⁺ T cell infiltration into the tumor. Inhibition of platelet PAR4 signaling increases calcium signaling through an estrogen-dependent interaction between PAR4 and estrogen receptor β (ERβ)—a receptor interaction not previously described. PAR4-activated platelets within the TME suppress CD8⁺ T cell function, and depletion of CD8⁺ T cells abolishes both the tumor-induced platelet reactivity and the survival benefit conferred by PAR4 inhibition. These findings establish platelet-mediated PAR4 signaling as a critical driver of tumor progression and identify sex-specific immune responses as key to therapeutic efficacy.

Background Delirium is a state of acute brain failure causing confusion, reduced focus, and changes in alertness. It is common in older patients, occurring in 6-38% of older emergency department (ED) patients. Evidence suggests that systematic screening improves detection rates and early detection, management and reporting are critical. However, examples of operationalizing this in clinical non-research care are scarce. Objective To describe and disseminate examples of best practices for delirium screening, management, and monitoring within the ED. Methods A group of emergency physicians interested in geriatric emergency medicine (GEM) and evidence-based medicine gathered monthly to discuss ways of implementing delirium care. Members were asked to submit any electronic health record (EHR)-based interventions for delirium in current use at their institutions. One group member categorized the EHR tools by their use for screening, prevention, management, and monitoring of delirium. As a group, categorizations were reviewed and agreed upon and similarities, differences and themes were identified. Results Current EHR interventions from 5 EDs were included. We found that: 1) Screening for delirium in EDs is challenging due to the nature of the environment and the variety of tools available. 2) Prevention tools included order sets. 3) Management was accomplished with best practice alerts and order sets to help screen, prevent, address underlying causes, and manage agitation. Delirium prevention order sets emphasize optimizing patient mobility, comfort, and communication. Assessment order sets include routine labs and consultations, while management order sets for agitation provide safe medication options considering older adults’ unique physiology. 4) Utilizing dashboards for compliance monitoring offers real-time feedback, and provides an overview of adherence to clinical guidelines, regulatory standards, and patient safety protocols. Conclusion These real-world examples can be used in EDs implementing delirium programs. Further studies on how EHR interventions impact screening, diagnosis, and treatment of delirium in the ED are needed.

Background & objectives Antimicrobial resistance has steadily become a grave public health problem worldwide, making carbapenems, often the last choice of antibiotic, for treating infections involving multidrug-resistant Gram-negative organisms. The production of carbapenemases is one of the primary mechanisms responsible for the development of resistance. KPC, NDM, VIM, IMP, and OXA-48-like are the most prevalent carbapenemases. Identification of CROs is based on the resistance phenotype or requires molecular assays, which are not widely available. A lateral flow assay (LFA) has been developed to enable rapid identification of carbapenemase production in cultured bacteria. Methods A total of 87 isolates characterised by Whole Genome Sequence (WGS) were tested. Five ATCC strains were used for quality control. LFA was performed according to the kit literature, and the results were compared with those by WGS. The assay was assessed for its sensitivity and specificity for the detection of five major carbapenemases. Results A total of 87 isolates of Enterobacterales and Pseudomonas aeruginosa, characterised by WGS, were tested. Of these, 52 were positive for the big five carbapenemases (IMP, VIM, KPC, NDM, and OXA-48-like), and 35 were negative. ATCC strains were run for quality control with each batch of tests. Overall sensitivity of the assay was 98.07 per cent (51/52), with no false positives, having 100 per cent specificity (35/35). The assay correctly detected strains producing KPC, OXA-48-like, VIM, and IMP, being 100 per cent sensitive (n=33/33) when compared with WGS results; whereas, it showed delayed positivity (>15 min) to identify one strain producing NDM-1 (thus considered false negative), accounting to sensitivity of 92.3 per cent (n=12/13) for detection of NDM. It correctly identified six strains simultaneously producing OXA-48-like and NDM, and one strain producing NDM-1 and KPC. Interpretation & conclusions The assay, being robust and cost-effective, with a short turn-around-time, will prove to be a great addition to the diagnostic armamentarium, helping in implementing antimicrobial stewardship and preventing AMR.

Key Points We characterized the renal transcriptional profile at the single-nuclear level in a preclinical swine model of CKD. Our study reveals that renal endothelial cells represent the cluster with the highest number of differentially expressed genes related to inflammatory and fibrotic activity. These results offer new insights into CKD-induced transcriptional changes in renal endothelial cells at the single-nuclear level. Background The prevalence of CKD is on the rise, and precision strategies to offset the progression to ESKD are needed. We used a well-established preclinical translational model of CKD in swine and single-nucleus RNA sequencing (snRNA-seq) to identify potential therapeutic targets through characterization of the renal cell-specific transcriptomic landscape. Methods Normal and CKD pigs were studied in vivo and ex vivo after 14 weeks ( n =6/group). In randomly selected pigs ( n =3/group), kidneys were harvested, nuclei isolated, libraries prepared, and snRNA-seq performed. Protein expression of candidate differentially expressed genes (DEGs, log2FC >0.25, adjusted P value < 0.05) was determined by immunohistochemistry, and their expression in primary normal and CKD renal vascular endothelial cells was modulated (small interfering RNA) in vitro . Results A total of 52,213 nuclei were analyzed. Thirty clusters were identified and filtered by canonical gene markers, revealing 16 unique renal cell types. Endothelial cells were the top cell type exhibiting the highest number of DEGs, which were subsequently filtered by angiogenesis, inflammation, and fibrosis (major injurious pathways altered in CKD kidneys). Venn diagram analysis identified five unique overlapping DEGs in endothelial cells: vWF , LAMA3 , and KDR upregulated and PTGIS and ICAM1 downregulated in CKD versus normal kidneys. Venn diagram analysis indicates that vWF , LAMA3 , and ICAM1 participate in inflammatory and fibrotic signaling. Renal protein expression of these DEGs matched snRNA-seq findings. Furthermore, in vitro silencing of vWF and LAMA3 ameliorated endothelial cell inflammatory and fibrotic signaling. Conclusions Our work characterized the single-nuclear renal cell transcriptomic landscape of a translational model of CKD and singled out genes implicated in major renal injury pathways. These genes could serve as potential targets to pave the way for new therapeutic strategies in patients with CKD.