Citations

Abstract Glioblastoma (GBM) is a lethal, treatment-resistant brain cancer characterized by diffuse brain invasion, complex neuron-glioma signaling, and cellular, molecular, and spatial heterogeneity. Surgery is the current mainstay of treatment, aimed at maximizing tumor cytoreduction, decompressing the brain to improve neurological function, and providing material for analyses to inform prognostication and adjuvant treatment selection. To accurately model GBM surgical resection and tissue sampling in preclinical animal models, we developed the Maximal Safe Intracranial Surgery (MSIS) system. MSIS integrated a miniaturized neurosurgical resection device and enabled a safe, tunable, and reproducible approach for intracranial tumor resection, multi-regional biopsy, and longitudinal tissue sampling in murine models, with stereotactic, sterile, and high-viability tissue collection. MSIS was applied across five distinct orthotopic brain tumor models to reproducibly generate histologically and radiologically representative models of post-surgical GBM. Similar to humans, increasing the extent of resection correlated with improved animal survival, and recurrent growth patterns varied significantly by model type. Transcriptional profiles of matched primary vs. post-surgical recurrent tumors revealed enrichment of margin-associated transcriptional states consistent with neuron-glioma signaling. Overall, the MSIS system offers opportunities to model the standard-of-care, dissect the spatial and temporal dynamics of GBM, and pair therapeutic discovery with contextual tumor pathobiology.

ABSTRACT Background Evaluating fairness in artificial intelligence (AI) is essential before clinical implementation to prevent unintended harm across diverse patient populations. This study assesses performance differences of an image-based surgical site infection (SSI) detection model across age, gender, geography, race, and skin color. Methods Model development/validation study using retrospective, multicenter data across surgical subspecialties from adults who submitted an image of their incision via the electronic health record within 30 days of their procedure between 2019-2024. Area under receiver operating curve (AUROC) was compared by age (<55 vs. ≥55 years old), gender (male vs. female), geography (Rochester, Minnesota vs. Jacksonville, Florida vs. Scottsdale, Arizona vs. regional Minnesota/Wisconsin areas), race (White/Caucasian vs. non-White/Caucasian), and skin color (Fitpatrick I-III vs. IV-VI and Monk A-E vs. F-J). Results Training data contained 13,702 images from 4,274 patients between 2019-2022 (50.1% ≥55 years old; 63.2% female; 91.6% White/Caucasian; 58.5% Rochester, 17.3% Florida, 10.5% Arizona; 96.3% light skin tone), of which 1,348 images (9.8%) had an SSI. No differences in SSI detection existed for age, gender, race, or skin color (AUROC 0.83-0.87, p>0.09), however geographical differences were significant: lowest AUROC 0.83 (95% CI 0.77-0.88) vs. highest AUROC 0.87 (95% CI 0.84-0.89, p=0.01). Temporal validation using 4,242 images from 1,353 patients between 2022-2023 showed intact fairness across subgroups (ΔAUROC ≤0.06) except geography (ΔAUROC ≤0.16). Conclusions The model behaved fairly across age, gender, race, and skin color, however geographical differences persisted. These findings have practical implications underscoring the importance of evaluating bias in clinical AI before deployment.

Abstract Purpose Validate the semiquantitative (SQ)-MRI score for chronic pancreatitis (CP) diagnosis in an independent, multicenter cohort. Methods We analyzed MRIs performed at baseline in 337 participants with acute (AP) or recurrent AP (RAP) and 67 with non-calcific chronic pancreatitis (NCCP) enrolled in the PROCEED study from 6/2017 to 3/2023. MRIs were performed at multiple clinical centers using site-specific clinical protocols and a variety of MRI vendors to evaluate the SQ-MRI score in a real-world setting. The SQ-MRI score was calculated using the T1 signal intensity ratio of the pancreas to the spleen (T1 score), arteriovenous enhancement ratio (AVR), and pancreatic body diameter (PBD). We adjusted for confounding by participant characteristics via propensity score weighting. Results Median AVR was higher in AP/RAP (1.18, IQR: 0.97–1.44) than in the NCCP group (1.03, IQR: 0.78–1.22, p = 0.007). Pancreatic body diameters were larger in AP/RAP than in the NCCP group − 7–14 mm (10% vs 25%), 14–20 mm (40% vs 54%), and > 20 mm (50% vs 21%), respectively ( p < 0.01). Median T1 score was higher in AP/RAP (1.18, IQR: 0.96–1.40) than in the NCCP group (1.04, IQR: 0.86–1.32, p = 0.10). Median SQ-MRI score in the AP/RAP group was significantly lower, 1.91 (IQR: 0.97, 2.95), than in the NCCP group, 2.74 (IQR: 2.04–4.03) ( p < 0.001). The propensity score-adjusted AUC for SQ-MRI to distinguish AP/RAP from NCCP was 0.64, which was higher than for individual parameters. Conclusion We have validated the SQ-MRI score in a multicenter cohort using an independent, real-world MRI dataset.

ABSTRACT Introduction Postoperative mortality commonly follows complications that are not prevented, recognised or managed effectively. Ward‐based nursing care is central to surveillance, escalation and rescue, but population‐level evidence using shift‐level staffing data is limited. This national population‐based cohort study examined the association between surgical ward nurse staffing and postoperative outcomes. Methods Adults aged 18 years or older undergoing inpatient surgery under general or neuraxial anaesthesia in public hospitals in Aotearoa New Zealand between 2022 and 2024 were included. Prospectively recorded TrendCare staffing data were linked to administrative health datasets. The exposure was shift‐level staffing variance, defined as the difference between required and available nursing care hours on surgical wards in the treating hospital during admission. The primary outcome was 90‐day postoperative mortality. Secondary outcomes were postoperative complications and failure to rescue. Results The cohort included 202 428 patients undergoing 223 415 surgical admissions. Within 90 days, 6296 admissions resulted in death (2.8%). Complications occurred in 41 722 admissions (18.7%), with failure to rescue in 15.1%. Of 281 147 surgical ward shifts, 122 186 (43.5%) were understaffed. After adjustment, each one‐nurse reduction in staffing per shift was associated with higher odds of mortality (aOR: 1.13, 95% CI: 1.07–1.18), complications (aOR: 1.07, 95% CI: 1.05–1.10) and failure to rescue (aOR: 1.07, 95% CI: 1.00–1.14). Modelling estimated that correcting observed staffing deficits was associated with 182 fewer deaths annually. Conclusion Lower surgical ward nurse staffing was associated with increased postoperative mortality, complications and failure to rescue. Nurse staffing is a modifiable system factor associated with postoperative safety and should be prioritised to improve surgical outcomes.

ABSTRACT Background Radiotherapy is a cornerstone of treatment for pediatric central nervous system (CNS) tumors, but dose selection remains uniform despite interpatient variability in tumor radiosensitivity. This is consequential in children, for whom toxicity can have lifelong effects. Genomic-adjusted radiation dose (GARD) integrates tumor genomics with delivered radiation dose to quantify the biological effect of radiotherapy and has been validated across adult malignancies. Its relevance in pediatric CNS tumors is unknown. Methods We performed a cohort study using gene expression and data from 246 pediatric patients with high-grade glioma, medulloblastoma, or ependymoma from the Children’s Brain Tumor Network. GARD was calculated using a sequencing-adapted radiosensitivity index integrated with radiation dose through the linear–quadratic model. Associations of GARD and physical radiation dose with event-free and overall survival were evaluated using Cox proportional hazards models stratified by tumor type and anatomic location. Patients who did not receive radiotherapy comprised a negative control cohort (sham-GARD). Results Among patients receiving radiotherapy, physical dose was uniform, whereas GARD showed substantial interpatient variability in biological effect. Higher GARD was associated with improved event-free survival (hazard ratio [HR] 0·90, 95% CI 0·83–0·97; p=0·004) and overall survival (HR 0·90, 95% CI 0·83–0·99; p=0·018). Physical dose was not associated with either endpoint. Among patients who did not receive radiotherapy, sham-GARD was not associated with outcomes, supporting GARD as a treatment-specific predictor rather than a prognostic biomarker. Conclusions In pediatric CNS tumors, the biological effect of radiotherapy quantified by GARD was associated with outcomes, whereas physical dose was not. These findings challenge uniform radiotherapy dosing and support genomically informed dose individualization. Prospective evaluation of GARD-guided radiotherapy is warranted to optimize tumor control while minimizing long-term toxicity in children.

Deregulated inflammatory signaling via STAT family transcription factors, particularly STAT1, underlies a variety of immune-related diseases, including inflammatory bowel disease. Whereas activation of STATs by JAKs via canonical receptor-driven JAK–STAT signaling is well understood, little is known about JAK-independent mechanisms of STAT activation. Here, we identify the understudied nonreceptor tyrosine kinase TNK1 as a therapeutically targetable, JAK-independent activator of STAT signaling. Using a multiomics approach, we mapped a network of TNK1 substrates associated with protein condensates and proinflammatory signaling, including STAT1. We found that TNK1, but not its sister kinase ACK1, directly phosphorylates STATs at well described STAT-activating JAK sites. In cells, TNK1-mediated STAT1 phosphorylation and activation occurs independently of JAKs. Imaging and interactomics data suggest that TNK1 interacts with STAT1 in cytosolic condensates, which likely compartmentalize TNK1-substrate interactions. We show that an intrinsically disordered proline-rich region in TNK1, which includes a 14-3-3 docking phosphorylation site, is required for the formation of kinase-active TNK1 condensates and STAT1 phosphorylation. Mutations within the proline-rich region that eliminate 14-3-3 binding increase formation of TNK1 condensates, suggesting a model in which 14-3-3 acts as a clamp that constrains the flexible PRR to inhibit condensate formation and STAT1 activation. Finally, we show that TNK1 is a targetable driver of STAT1-mediated inflammation in the gut as inhibition of TNK1 reduces active STAT1 in the colon and ameliorates colitis symptoms in mice.