Citations

Abstract Background Glioblastoma (GBM) is driven, in part, by glioma stem cells (GSCs), which sustain therapeutic resistance and recurrence. OLIG2 is a key regulator of GSC programs but the signaling pathways that cooperate with Oligodendrocyte transcription factor 2 (OLIG2) to maintain GSC states remain incompletely defined. Although Signal transducer and activator of transcription (STAT) signaling has been implicated in GSC biology, work to date has focused primarily on STAT3, and the contribution of STAT5 remains poorly defined. Here, we investigated whether STAT5B functionally cooperates with OLIG2 in sustaining GSC phenotypes. Methods Transcriptomic analyses, proximity ligation assays and biochemical studies were utilized to define OLIG2-STAT5B interactions in patient-derived GSCs. Functional consequences of OLIG2, STAT5B, BIRC5, and NUSAP1 suppression were assessed using small interfering RNA/short hairpin RNA-knockdown, stemness, and migration assays in EGFRvIII-expressing GSCs. In vivo tumor growth studies were performed using orthotopic xenograft models. Results OLIG2 and STAT5B expression were positively correlated in GBM datasets and patient-derived models. OLIG2 physically associated with STAT5B in EGFRvIII-expressing GSCs, and loss of OLIG2 reduced STAT5 activation, supporting a functional link between these factors. OLIG2 or STAT5B suppression induced convergent transcriptional changes, including downregulation of genes associated with GSC maintenance and proliferation, notably stemness regulators BIRC5 and NUSAP1. Silencing BIRC5 or NUSAP1 impaired GSC self-renewal and migration. In orthotopic models, STAT5B knockdown prolonged survival and phenocopied OLIG2 suppression and stemness loss. Conclusions These findings identify STAT5B as a functional partner of OLIG2 in GBM and define anOLIG2-STAT5B transcriptional axis that sustains GSC maintenance and malignant behavior. Targeting this axis may represent a therapeutic strategy to disrupt treatment-refractory glioma cell states.

ABSTRACT Aims Exercise capacity is a powerful predictor of cardiovascular risk. In patients unable to exercise, body composition analysis can potentially be used to estimate cardiorespiratory fitness. We developed a body composition “fitness” score, then validated its utility in two external populations. Methods and Results We included patients from four sites undergoing single photon emission computed tomography (SPECT) and twelve sites undergoing positron emission tomography (PET). We quantified body composition using deep learning. We evaluated associations between body composition and good exercise capacity (defined as completing ≥7 minutes on a Bruce protocol) then developed a body composition “fitness” score. We then assessed the associations of “fitness” score with exercise capacity and all-cause mortality in external populations. In total, 36471 patients were included with median age 67 (interquartile range 58 – 74). Median skeletal muscle density was higher among patients with good exercise capacity. In the external SPECT population, the body composition “fitness” score had higher prediction performance for good exercise capacity (AUC 0.771, 95% CI 0.752 – 0.789) than age (AUC 0.717, p<0.01). In the external PET population, high body composition “fitness” score was associated with lower cardiovascular death (adjusted hazard ratio 0.70, 95% CI 0.62 – 0.79, p<0.001). Conclusions We demonstrated that a comprehensive body composition “fitness” score could identify patients with good cardiorespiratory fitness. This approach transforms routinely acquired CT data into a surrogate marker of fitness which can be applied in patients undergoing PET, or other CT imaging, where exercise testing is not performed. Graphical Abstract Overview of study design. The overall population (n=36471) was split as outlined above. Body composition was analyzed from available computed tomography imaging. The distribution of body composition measures were analyzed in the combined single photon emission computed tomography (SPECT) populations. A body composition “fitness” score was derived to predict good exercise capacity in the internal population, with associations assessed in the two external testing populations.

Abstract Human genomic studies link reduced CUB domain-containing protein 1 (CDCP1) expression with myocardial recovery in heart failure. While CDCP1 regulates cardiac fibroblast proliferation in vitro, it’s in vivo role in cardiac fibrosis remains unclear. Using a Cdcp1 -knockout (KO) angiotensin II/phenylephrine mouse model, we show that Cdcp1 deletion reduces echocardiographic left ventricular mass, histologic cardiac fibrosis, and pro-fibrotic gene expression, along with decreased fibroblast activation and inflammatory markers. Spatial transcriptomics identified a pressure overload–expanded fibroblast subpopulation enriched for growth factor and TGF-β signaling (FB5), which was markedly attenuated in Cdcp1 -KO hearts, alongside reduction of a pro-inflammatory cardiomyocyte subtype (CM4). Complementary studies in human ventricular fibroblasts demonstrate that CDCP1 knockdown reduced extracellular matrix gene expression and collagen I deposition. These findings establish CDCP1 as a regulator of cardiac fibrotic remodeling in vivo and open avenues for its further investigation as a potential therapeutic target.

Abstract Background and aims Interfacility transfers in rural areas are challenging due to limited ambulance and bed availability, image sharing issues, and access disparities. Regional transfers to strategically located primary stroke centers can reduce time to care, decrease helicopter use, support local economies, and conserve comprehensive stroke center (CSC) resources. This study established a primary stroke center as a regional transfer center (rSTC) within a telestroke network. Methods Over one year, stakeholders created regionally appropriate transfer workflows defined as patients without large vessel occlusion, low likelihood for neurosurgical decompression or critical illness within a rSTC and 4 surrounding centers. Continuous education and prospective case logs were maintained by the rSTC stroke coordinator and a retrospective chart review was conducted one year following the intervention period. Results Of 99 patients requiring transfer, 73 (73.7%) went to the rSTC, with an average stay of 2.1 days, no deaths, and no secondary CSC transfers. The remaining 26 (26.3%) were sent to the CSC, with longer stays (10.6 days) and higher mortality (23.1%). Transfers to the rSTC were faster (60 min vs. 188 min). Financial analysis showed significant EMS savings ($455,111) and local health system benefits ($730,000) when compared to the pre-intervention period. Conclusions Establishing an effective regional transfer model is possible with broad stakeholder engagement and regular network maintenance. rSTCs provide the right level of care for the right patient, improving efficient allocation of healthcare resources and avoiding futile transfers with costly admissions far from home while opening beds and reducing transfer times to CSCs. Conflict of interest Nothing to disclose

ABSTRACT Objective To evaluate intracochlear electrocochleography (ECochG) amplitude parameters during cochlear implantation (CI) using a novel multi‐frequency ECochG algorithm. Methods A multi‐institutional, prospective cohort study was performed at 18 high‐volume CI centers. The inclusion criteria were adults with sensorineural hearing loss and audiometric thresholds of ≤ 90 dB hearing level at 500 Hz undergoing CI with Advanced Bionics (Valencia, CA) Ultra 3D devices between 2024 and 2025. ECochG recordings were performed with simultaneous multi‐frequency stimulation of four frequencies between 125 and 4000 Hz during cochlear implant insertion. Concurrent multi‐frequency recording allowed extraction of amplitude and phase of each frequency individually. Post hoc analysis was performed to determine the difference in the number of drop alarms between single‐ and multi‐frequency ECochG. An ECochG amplitude drop of 6 dB was defined as a drop alarm. Insertion track patterns were compared between single‐ and multi‐frequency ECochG. Results One hundred ninety‐five ears were included. Mean number of drop alarms for the single‐frequency algorithm was 1.72 (95% CI: 1.52, 1.92; median 1) compared to 0.42 (95% CI: 0.31, 0.53; median 0) for multi‐frequency; p < 0.001. The number of Type C patterns (rise in amplitude during insertion followed by a drop) decreased with the multi‐frequency ECochG algorithm compared to the single‐frequency ECochG algorithm. The number of Type D patterns (no‐response) decreased, indicating that multi‐frequency ECochG generated more responses across the cochlea than single‐frequency ECochG. Conclusions A novel multi‐frequency ECochG algorithm during CI is associated with fewer drop alarms and altered insertion track patterns, which may provide a more accurate assessment of the cochlear microenvironment. Level of Evidence 3.

Abstract Neurosurgical and neuromodulation therapies such as deep brain stimulation (DBS) require millimeter-level accuracy to effectively target functional brain regions. Yet, many neuroanatomical boundaries remain invisible to current imaging and electrophysiology methods, limiting precision and contributing to suboptimal patient outcomes. Here, we introduce a self-supervised artificial intelligence (AI) framework that learns to delineate functional subregions directly from the spectral content of intraoperative local field potential (LFP) recordings, without the need for predefined biomarkers or anatomical labels. The framework identifies physiologic structure across the full spectrum of the signal and, through explainable AI (XAI), reveals the specific frequency components underlying these distinctions. Validated in the subthalamic nucleus (STN), the model aligned with clinically defined borders and rediscovered known beta oscillations. Applied to the motor thalamus in tremor patients, it consistently identified functional transitions corresponding to the ventral oralis posterior (Vop) and ventral intermediate (Vim) nuclei—regions where conventional methods fail to provide reliable boundaries. To assess clinical relevance, physiologically defined clusters were functionally evaluated using monopolar review data at their first DBS clinic postoperative visit, demonstrating distinct stimulation-response profiles across clusters and linking electrophysiologic segmentation to clinically meaningful programming outcomes. These findings demonstrate that intraoperative LFP recordings can be transformed into both a real-time guidance resource and a data-driven platform for biomarker discovery, establishing a foundation for more precise, individualized neuromodulation therapies and advancing our understanding of functional brain organization.

PURPOSE Most oncology trials define superiority according to dichotomized P value thresholds, which are frequently misinterpreted. Posterior probability, however, directly estimates the probability of the hypothesis at hand. Here, we reanalyze a large collection of modern phase III trials and benchmark posterior probability versus the standard trial interpretation based on statistical significance. METHODS Outcomes from 194,129 patients were manually reconstructed from the primary end points of 230 phase III, superiority-design oncology trials. Posterior probabilities of treatment effect were then calculated across multiple priors and several effect sizes of clinical relevance, including minimum clinically important difference (MCID) defined as hazard ratio (HR) < 0.8 per ASCO criteria or HR < 0.64 per European Society of Medical Oncology (ESMO) criteria. RESULTS All trials interpreted as superior using P value thresholds had probabilities >90% for achieving at least marginal benefits (HR < 1). However, only 62% of positive trials (74/120) had >90% probabilities of achieving the ASCO MCID (HR < 0.8), even under an enthusiastic prior, including 70% of trials (57/82) leading to regulatory approval. Only 30% of positive trials (36/120) had >90% probability of achieving the ESMO MCID (HR < 0.64). Conversely, 24% of trials (26/110) interpreted as not superior had >90% probability of achieving marginal benefits (HR < 1), even under a skeptical prior. CONCLUSION Bayesian models, although often in agreement with statistical significance thresholds, add considerable unique interpretative value for a subset of phase III oncology trials. Posterior probability may provide a solution for overcoming the discrepancies between refuting the null hypothesis and detecting clinically relevant effects.

ABSTRACT Background and Objectives NCCN guidelines recommend right hemicolectomy (RHC) for appendiceal neuroendocrine tumors (aNETs) > 2 cm and observation for < 1 cm. However, optimal surgical management of 1–2 cm tumors remains controversial. This study compared long‐term survival and recurrence between patients undergoing RHC versus appendectomy (APY) for 1–2 cm aNETs. Methods Patients with pathologically confirmed 1–2 cm aNETs treated at three Mayo Clinic sites (1972–2024) were included. Primary outcomes were recurrence and all‐cause mortality after resection. Associations with lymph node (LN) metastasis were assessed in patients with lymphadenectomy. Results Sixty‐five patients were identified: 29 (45%) underwent APY, 35 (54%) RHC, and one ileocecectomy. Median age at diagnosis was 39 years; 71% were female and 94% white. LN positivity was 15.2% for tumors with nodes examined. Tumor size > 1.5 cm, stage T3/T4, and lymphovascular invasion were not associated with nodal metastasis. No survival differences were observed between APY and RHC. LN positivity did not impact survival. No recurrences occurred during a median follow‐up of 6.25 years (IQR 2.44–12.63). Conclusions Among patients with 1–2 cm aNETs, RHC conferred no survival benefit over APY. Absence of recurrence and the limited prognostic value of nodal disease suggest APY alone may suffice for this population.