Citations

The immune tumor microenvironment (iTME) plays a crucial role in disease biology of plasma cell (PC) dyscrasias, but remains poorly characterized in self-identified Black individuals, a population at increased risk. Mass cytometry and scRNA-seq of 128 bone marrow aspirates revealed significant changes in immune cell composition across the disease spectrum, including shifts from naïve to effector T cells with declines in B cells, MAIT, pDCs, and increases in monocytes with disease progression. Self-identified Black patients had higher relative proportions of terminally differentiated T cells and lower monocytes in newly diagnosed and treated multiple myeloma (MM). ScRNA-seq revealed genes overexpressed in self-identified Black individuals were enriched for E2F targets and G2-M checkpoints, while reduced genes were enriched for TNF-α/NF-kB, interferon and inflammatory responses pathways. These findings were supported by genetic ancestry and validated in an independent dataset of 286 patients with MM from the MMRF Immune Atlas. Self-identified race and African genetic similarity are significantly associated with remodeling the MM iTME, with potential implications for disease biology and treatment response.

Introduction Functional hypothalamic amenorrhea (FHA) accounts for 30% of secondary amenorrhea and is characterized by hypothalamic hypercortisolemia, hypothalamic hypothyroidism, and anovulation with hypoestrogenemia due to disrupted GnRH drive. While FHA is associated with decreased bone mineralization; it remains unclear how bone health compares to menopausal women, who also experience bone loss. This study compared dual-energy x-ray absorptiometry (DXA) bone health parameters among women with FHA, eumenorrheic controls, and recently menopausal women. It also examined the impact of prior combined oral contraceptive (COC) use on bone mineral density (BMD) in women with FHA. Methods This cross-sectional study included 20 women with FHA, 9 eumenorrheic controls, and 12 recently menopausal women who underwent hip and spine DXA. None of the participants were taking hormone therapy. FHA was defined as ≥3 months of amenorrhea, estradiol <50 pg/ml, FSH and LH <10 mIU/L, excluding other etiologies. DXA bone parameters were measured using Lunar iDXA (GE) including BMD from lumbar spine (L1-L4) and hip. Results By design, age differed significantly across groups (p < 0.0001), with median ages of 27.8 years [23.4, 34.1] in women with FHA, 29.6 years [28.3, 32.4] in eumenorrheic controls, and 55.3 years [53.5, 56.6] in recently menopausal women. There were no significant differences in weight or BMI across groups. Significant differences were observed at all measured skeletal sites, including all lumbar spine levels, femur neck, total femur, and total BMD (all p < 0.05). Pairwise comparisons revealed that lumbar spine BMD was significantly lower in FHA compared to eumenorrheic controls (p = 0.04), while FHA and menopausal women did not significantly differ from each other (p = 0.07). Among FHA women with prior COC use, L1–4 BMD was not significantly different from controls (p = 0.19). Conclusions Lumbar spine BMD in young women with FHA was comparable to that of recently menopausal women, highlighting the profound skeletal impact of chronic estrogen deficiency. Prior COC use may partially attenuate FHA-associated bone loss, though larger studies are needed to confirm this observation. Future studies should explore whether skeletal outcomes vary by FHA etiology and the potential role of COC duration in preserving BMD.

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

➢ Periprosthetic joint infection (PJI) remains the most common cause of failure after total joint arthroplasty, with current standard therapies associated with failure rates between 10% and 30%. ➢ The 2025 International Consensus Meeting in Istanbul, Türkiye, highlighted the potential benefits of bacteriophage (phage) therapy in managing PJI. ➢ One of the barriers to integrating phage therapy into standard clinical PJI care is the knowledge gap between preclinical research and clinical practice. ➢ This Expert Review summarizes the key therapeutic advantages of using phages as an adjuvant therapeutic platform for PJI. It also highlights the current challenges that are continuing to limit the integration of phages into standard PJI care.

Importance Ischemic heart disease (IHD), the leading cause of death in the US, is predominantly due to modifiable risk factors. Estimates of IHD mortality attributable to risk factors provide evidence for health policy decision-making. Objective To estimate the burden of IHD death attributable to risk factors in the US from 1990-2023. Design, Setting, and Participants The Global Burden of Disease Study 2023 (GBD 2023) used vital records and a broad set of epidemiologic data to estimate IHD death rates, risk factor exposure, and relative risk curves for risk-outcome pairs for 1990-2023 for the general population. Data analysis was performed from October 2024 to December 2025. Exposure Twelve metabolic, behavioral, and environmental risk factors. Main Outcomes and Measures The primary outcomes were IHD death rates per 100 000 persons, counts, and attributable risks from 1990-2023 by age, sex, and US state. Estimates include 95% uncertainty intervals (UI). IHD death rates were estimated using ensemble modeling methods. Risk exposures were estimated using bayesian meta-regression methods. Relative risks were estimated following the Burden of Proof framework. Results In 2023, there were 473 000 IHD deaths (95% UI, 414 000-510 000) in the US, a decrease of 58.7% (95% UI, 56.8%-61.0%) in age-standardized rate since 1990. Between 2010 and 2023, there was a 19.0% decrease (95% UI, 15.0%-22.9%) for males and a 24.5% decrease (95% UI, 20.3%-29.7%) for females in IHD death rates. High systolic blood pressure (SBP), dietary risks, and high low-density lipoprotein cholesterol (LDL-C) were the leading risk factors for IHD deaths in 2023, accounting for 47.2% (95% UI, 36.4%-57.0%), 38.6% (95% UI, 17.2%-56.8%), and 28.5% (95% UI, 19.3%-39.6%) of IHD deaths, respectively. Increased exposure to several risk factors substantially increased their attributable burden for IHD deaths in 2023, with high fasting plasma glucose (FPG) increasing 38.8% (95% UI, 11.5%-81.1%) and high body mass index (BMI) increasing 54.5% (95% UI, 41.8%-66.3%) since 1990. Smoking and particulate matter pollution had the greatest decrease in attributable IHD mortality since 1990, at 33.3% (95% UI, 23.6%-41.7%) and 74.9% (95% UI, 46.7%-88.8%), respectively. Conclusion and Relevance Per the results of this systematic analysis of GBD 2023, a total of 88.7% (95% UI, 83.4%-92.5%) of IHD deaths were attributable to modifiable risk factors in the US in 2023, with high SBP, dietary risks, and high LDL-C being the greatest contributors. High BMI and high FPG showed the largest attribution increases, while exposure to other risks did not increase significantly for the population.

Abstract Embryonal tumors with multilayered rosettes (ETMR) are rare, highly aggressive tumors of infancy with extremely poor outcomes and no established standard of care therapy. ETMRs were recognized as a distinct molecular entity in 2016, however, the absence of prospective, biology-driven clinical trials has limited translation of these insights into standardized, risk-adapted treatment approaches for this vulnerable population. To address this gap, the Collaborative Network for Neuro-oncology Clinical Trials (CONNECT) developed CURE(Clinical trial advancing Understanding of Rare Embryonal Brain Tumors), an international, multi-institutional, molecularly guided umbrella trial. All patients enroll through the centralized CURE-Screening protocol, which provides rapid comprehensive molecular profiling with real-time central pathology, molecular, and radiographic review to confirm diagnosis, define molecular subtype, and determine eligibility and assignment to disease-specific treatment arms. CURE-ETMR represents the first disease-specific arm to open within this platform. Following centralized screening, children with newly diagnosed ETMR are assigned to clinically defined risk strata using integrated molecular, radiographic, and clinical criteria. Patients will be treated using a risk-adapted multimodal approach in which we prioritize maximal safe surgical resection with consideration of second-look surgery based on centralized imaging review; administer induction chemotherapy followed by consolidation with high-dose chemotherapy and autologous hematopoietic cell rescue or dose-intensified chemotherapy, selectively incorporate radiation sparing approach or early focal radiotherapy for patients with unresectable residual disease or brainstem involvement; deliver intrathecal chemotherapy for leptomeningeal prophylaxis; and include biologically informed maintenance therapy. In parallel, protocol-required longitudinal collection of tumor tissue, cerebrospinal fluid, blood, and advanced neuroimaging supports integrated molecular, liquid biopsy, and imaging biomarker analyses to identify predictors of treatment response, resistance, and relapse. Primary objectives include evaluation of feasibility, safety, progression-free survival, and overall survival compared with molecularly annotated historical cohorts. This centralized screening to assignment framework establishes a scalable model for prospective, biology-driven trials in rare embryonal brain tumors.

Abstract Introduction: Surveillance biopsies after kidney transplantation provide an opportunity to assess early renal disease processes, including diabetic nephropathy, before clinical manifestation. This study aimed to identify proteomic alterations in renal allografts at 5 years post-transplant (5yrPT) and their associations with histologic features in diabetic/obese (DM/OB) versus non-diabetic/non-obese (nDM/nOB) recipients. Methods: We studied protocol biopsies from 17 DM/OB and 14 nDM/nOB kidney transplant recipients at Mayo Clinic (2000–2012). Laser capture microdissection followed by mass spectrometry was used for proteomic profiling. Histologic assessment included Banff and Tervaert scoring and morphometric analysis. Statistical comparisons were performed using ANOVA with Tukey post-hoc testing. Results: DM/OB recipients demonstrated greater histologic and metabolic injury at 5yrPT. Proteomic analysis identified 101 glomerular and 86 non-glomerular proteins differentially expressed between groups. Significant alterations were observed in proteins associated with mitochondrial dysfunction, including VDAC1 (fold change [FC] 2.6, p = 0.03), NDUFB9 (FC 0.15, p = 0.009), and NDUFA9 (FC 1.72, p = 0.01). Extracellular matrix remodeling proteins COL6A1, COL6A2, and COL6A3 were upregulated (FC 1.6–1.8, p < 0.05). Immune and inflammatory markers C9 (FC 1.6, p < 0.03) and TGFBI (FC 1.7, p < 0.001), as well as oxidative stress–related CLU, were increased. GGACT showed the greatest decrease (FC 0.30, p < 0.001), implicating altered energy metabolism. Conclusion: Distinct proteomic signatures at 5yrPT in DM/OB recipients highlight early mitochondrial, metabolic, immune, and extracellular matrix pathways involved in diabetic kidney disease. These changes precede clinical disease and identify candidate biomarkers and therapeutic targets to improve graft longevity.

e13656 Background: Effective multidisciplinary cancer care is bottlenecked by the cognitive burden of synthesizing fragmented electronic health records across different specialties. Current AI tools often function as isolated chatbots rather than integrated workflow assistants. We developed and validated "OncoSphere AI," an Agentic AI multidisciplinary clinical workflow support tool designed to autonomously orchestrate the multidisciplinary review process by deconstructing complex cases into domain-specific insights. Methods: OncoSphere AI is a novel, multi-agent large language model–driven platform that simulates a multidisciplinary tumor board for cancer care. The architecture uses a parallel reasoning framework in which eight virtual specialty agents—Medical Oncology, Radiation Oncology, Surgical Oncology, Pathology, Radiology, Pharmacy, Clinical Research, and Nurse Navigation—independently analyze structured and unstructured patient data against specialty specific guidelines and contemporary peer-reviewed literature. System performance was assessed via built-in telemetry (task completion, latency, inter-agent agreement) and blinded review by eight expert oncologists using a structured survey to rate data extraction fidelity, guideline concordance, safety, and clinical utility compared with standard manual review. Results: The study cohort (n=20, median age 59.5 years; 55% female) had a median of 2.5 (range 0-7) prior lines of therapy and multiorgan metastatic disease (median: 2, range 1–4), including lung, breast, gastrointestinal (CRC, pancreatic, hepatobiliary), and genitourinary (prostate, renal) malignancies. OncoSphere AI demonstrated high workflow utility (mean rating: 4/5) and strong extraction fidelity, with more than 90% of biomarker extractions rated as a “perfect match” by expert reviewers. Operational efficiency gains were substantial with AI processing averaged 4.7 minutes per case versus 29.3 minutes for manual review, corresponding to an 84% reduction in time (p<0.001). System telemetry revealed adaptive compute behavior, with the platform autonomously allocating 1.73-fold more reasoning tokens to complex, refractory cases than to standard scenarios. Safety review identified only one critical contraindication issue in a heavily pretreated, multi-line setting. Conclusions: OncoSphere AI effectively automates the clinical “perception layer,” consistently transforming heterogeneous longitudinal data into decision-grade insights with high fidelity and marked time savings. By operating as a coordinated ensemble of domain-specialized AI agents rather than a single generic model, it offers a scalable approach to reduce physician cognitive burden and to standardize guideline-concordant care planning in diverse, heavily pretreated oncology populations.

Background Burnout arises from prolonged, unresolved work-related stress and adversely affects professional performance and overall well-being. Resident doctors and medical students are particularly vulnerable because of the demands of balancing clinical, academic and related responsibilities. Aims This study aimed to assess self-reported burnout and related stressors among UK resident doctors and medical students, and estimate the economic impact of burnout-related absenteeism among resident doctors. Method Self-report questionnaires assessing burnout and related stressors were distributed to UK resident doctors and medical students. A total of 2793 responses were received: 1439 (51.5%) from resident doctors and 1354 (48.5%) from medical students. Economic losses from absenteeism were calculated with a human capital approach. Results Burnout was reported by 70% ( n = 1008) of resident doctors and 65.7% ( n = 889) of medical students. Notably, 56.8% ( n = 573) and 79.3% ( n = 705) of resident doctors and medical students affected by burnout, respectively, were unaware of available support services. Relocation stress (85.1% of residents and 62.6% of students), financial stress (53.9% of residents and 57.8% of students) and poor work–life balance (32.1% of residents and 20.7% of students) were commonly reported. The annual economic burden of absenteeism related to burnout among resident doctors was estimated to reach £251.5 million. Conclusions Burnout among UK resident doctors and medical students may reflect a combination of underlying factors, including financial strain, relocation stress and difficulties with work–life balance. These findings underscore the need for targeted interventions that support well-being and address financial and relocation challenges, which may, in turn, help prevent burnout and improve retention within the medical workforce. Reducing burnout and associated stressors may also help lessen its economic impact, allowing resources to be redirected towards patient care.