North Shore Diabetes and Endocrine Associates

Sepsis remains a leading global health challenge, characterized by high mortality and a persistent lack of disease-modifying therapies. Despite decades of investment, therapeutic progress has been constrained by reductionist strategies that target isolated pathogenic components. This perspective argues that these failures reflect a fundamental mischaracterization of sepsis-not as a disorder of discrete pathways, but as the collapse of complex biological systems in which normally coordinated processes become desynchronized. We identify the intermediate filament protein vimentin as a determinant of system fate governing the transition from adaptive host defense to pathological breakdown. Acting as a context-dependent network integrator and signal amplifier, vimentin coordinates antagonistic cellular programs by integrating biochemical and biophysical cues across immune, vascular, and metabolic systems. Under physiological stress, this coordination enables the orderly activation and resolution of inflammatory and suppressive responses required for pathogen control and restoration of homeostasis. In sepsis, persistent or excessive insults drive vimentin-mediated overactivation, uncoupling these programs and propagating systems-level instability that culminates in organ dysfunction. By integrating mechanistic, preclinical, and emerging clinical evidence, this perspective proposes vimentin modulation as a clinically translatable, systems-oriented strategy aimed at realigning host response networks to address the dynamic, opposing pathologies of sepsis that have eluded current therapies.

473 Background: KEYNOTE-564 demonstrated that adjuvant pembrolizumab improves outcomes after nephrectomy for clear-cell renal cell carcinoma (RCC). Whether this benefit extends to non–clear cell RCC (nccRCC) remains uncertain. We evaluated the association between adjuvant pembrolizumab and outcomes in patients with nccRCC who underwent nephrectomy in a multicenter study. Methods: We conducted a retrospective multicenter cohort study at six international institutions. Eligible adults had nccRCC treated with nephrectomy and were classified by receipt of adjuvant pembrolizumab. The primary endpoints were disease-free survival (DFS), defined as the time from nephrectomy to the first radiographic or clinical recurrence, and overall survival (OS), defined as the time from diagnosis to death or last follow-up. Survival functions were estimated with the Kaplan–Meier method and compared between groups using the log-rank test. Estimates of median DFS and OS were calculated using the Kaplan–Meier method. Results: Patient characteristics are shown in Table 1. Among 90 patients, 15 (17%) received adjuvant pembrolizumab, and 75 (83%) were observed; age at diagnosis was 56.0 years (IQR 44.0–63.0; mean 52.9 ± 13.1) and 62.0 years (IQR 52.0–71.0; mean 59.6 ± 14.7) respectively. Recurrence occurred in 7/15 (46.7%) with pembrolizumab and 25/75 (44.6%) with observation. There was no significant difference in median DFS (p = 0.75) or OS (p = 0.89) between groups. Median DFS was 90.7 months (95% CI, 27.2–NR) with pembrolizumab vs 41.9 months (95% CI, 39.4–NR) with observation; median OS was not reached (95% CI, 65.1–NR) with pembrolizumab vs 52.4 months (95% CI, 44.4–NR) with observation. Conclusions: In this descriptive retrospective six-center cohort of nccRCC post-nephrectomy, adjuvant pembrolizumab did not demonstrate a DFS or OS advantage over observation. A larger multi-institutional cohort is in progress to refine effect estimates using richer clinical detail, with adjusted analyses and prespecified subgroup assessment. Baseline characteristics by treatment group. Characteristic Overall (n=90) Observation (n=75) Pembrolizumab (n=15) Sex (Male/Female), n (ratio) 58 / 32 (1.8:1) 48 / 27 (1.8:1) 10 / 5 (2:1) T1, n (%) 11 (12.2%) 10 (13.3%) 1 (6.7%) T2, n (%) 10 (11.1%) 10 (13.3%) 0 (0.0%) T3, n (%) 64 (71.1%) 52 (69.3%) 12 (80.0%) T4, n (%) 3 (3.3%) 2 (2.7%) 1 (6.7%) Papillary RCC, n (%) 41 (45.6%) 36 (48.0%) 5 (33.3%) Chromophobe RCC, n (%) 31 (34.4%) 27 (36.0%) 4 (26.7%) Unclassified RCC, n (%) 7 (7.8%) 6 (8.0%) 1 (6.7%) Xp11 translocation, n (%) 8 (8.9%) 4 (5.3%) 4 (26.7%)

Network theory has proven invaluable in unraveling complex protein interactions. Previous studies have employed statistical methods rooted in network theory, including the Gaussian graphical model, to infer networks among proteins, identifying hub proteins based on key structural properties of networks such as degree centrality. However, there has been limited research examining a prognostic role of hub proteins on outcomes, while adjusting for clinical covariates in the context of high-dimensional data. To address this gap, we propose a network-guided penalized regression method. First, we construct a network using the Gaussian graphical model to identify hub proteins. Next, we preserve these identified hub proteins along with clinically relevant factors, while applying adaptive Lasso to non-hub proteins for variable selection. Our network-guided estimators are shown to have variable selection consistency and asymptotic normality. Simulation results suggest that our method produces better results compared to existing methods and demonstrates promise for advancing biomarker identification in proteomics research. Lastly, we apply our method to the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data and identified hub proteins that may serve as prognostic biomarkers for various diseases, including rare genetic disorders and immune checkpoint for cancer immunotherapy. R package is freely available on CRAN repository (https://CRAN.R-project.org/package=NetGreg) and published under General Public License version 3.

Upper tract urothelial carcinoma (UTUC) is a rare but aggressive malignancy where accurate preoperative assessment of tumour grade and stage is essential to guide treatment. Conventional tools such as ureteroscopic biopsy have limited accuracy and procedural risks. This systematic review evaluated the diagnostic and prognostic performance of radiomics models for predicting grade, stage, histotype, muscle invasion, and outcomes in UTUC. Following PRISMA guidelines (PROSPERO Registration ID: CRD420251141966), PubMed, EMBASE, CENTRAL, and grey literature were searched up to 6 September 2025. Eligible studies included radiomics-based analyses in adults with UTUC. Extracted performance metrics (AUC, sensitivity, specificity) were summarised as medians with ranges. Twelve studies (n = 1,685) were included, encompassing 45 distinct radiomics models: 20 for grade, 11 for stage, 10 prognostic, three histotype, and one for muscle invasion. Models predicting high-grade disease demonstrated excellent performance (median AUC 0.876, range 0.675–0.961; sensitivity 0.838; specificity 0.806). Prognostic models achieved a median AUC of 0.854 (range 0.750–0.933) and sensitivity of 0.909, effectively predicting recurrence-free and overall survival. Stage prediction models yielded a median AUC of 0.771 (range 0.711–0.860), while histotype models reported a median AUC of 0.84. The single study assessing muscle invasion achieved an AUC of 0.821. Most studies used CT-based radiomics with machine-learning classifiers, though validation methods and feature selection strategies were heterogeneous. Radiomics demonstrates high diagnostic and prognostic accuracy in UTUC, particularly for tumour grade and survival prediction. These findings support its potential as a non-invasive adjunct for risk stratification and surgical planning, though standardised multicentre validation is required before clinical adoption. The trial was prospectively registered on PROSPERO on 07/09/2025 under ID: CRD420251141966.

BackgroundX (formerly known as Twitter) is a social media platform with a robust online medical education community, including point-of-care ultrasound (POCUS) content.ObjectiveOur study aimed to determine if following curated POCUS education accounts on X translated to improved cardiac image interpretation competency.MethodsWe conducted an unblinded parallel-group randomized controlled trial at three internal medicine residency programs and two medical schools. Participants were third- and fourth-year medical students or internal medicine residents. They followed either 10 POCUS education accounts on X (T) or 10 generic medical accounts on X (C) for three months. Participants took a survey and a 15 multiple-choice question assessment before and after the protocol.ResultsTwenty-nine participants completed the protocol, 13 T and 16 C. Mean changes in image interpretation scores were T: -0.02% and C: +0.02%, which did not significantly differ (p = 0.46). A simple linear regression evaluating for correlation between average time spent on X and change in image interpretation scores among the T participants did not show a significant correlation (R squared – 0.0002, p = 0.96).ConclusionsNatural X exposure to educational POCUS accounts did not result in statistically improved image interpretation scores, but this outcome was likely affected by limited sample size, different participant experiences, and other variables. Data from this novel trial design can better inform future studies on medical education with social media.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12909-025-07385-3.