Citations

Renal dysfunction is highly prevalent among patients with cirrhosis and has major implications for management, prognostication, and liver transplant decision-making. Both acute kidney injury (AKI) and chronic kidney disease (CKD) occur frequently in this population and are driven by a complex interplay of hemodynamic derangements, systemic inflammation, and intrinsic or functional renal injury. Accurate assessment of kidney function is essential, as serum creatinine and estimated glomerular filtration rate (eGFR) calculations directly influence MELD-based transplant allocation, eligibility for simultaneous liver–kidney transplantation (SLKT), and clinical decisions such as drug dosing and peri-transplant immunosuppression strategies. However, creatinine-based assessments are fundamentally limited in cirrhosis due to reduced creatinine production, sarcopenia, expanded volume of distribution, increased tubular secretion, and assay interference from hyperbilirubinemia, resulting in frequent overestimation of true GFR. Alternative methods, including cystatin C-based equations, combined creatinine–cystatin C equations, timed urine clearances, and direct GFR measurement using exogenous filtration markers (iohexol, iothalamate), offer potential advantages but also carry important limitations, particularly in decompensated disease with ascites or inflammation. Newer cirrhosis-specific eGFR equations such as the GRAIL and Royal Free Hospital formulas attempt to address these shortcomings, yet validation studies demonstrate inconsistent accuracy across patient cohorts. This review summarizes the pathophysiologic contributors to renal dysfunction in cirrhosis, evaluates the performance and pitfalls of existing kidney function assessment tools, and highlights the ongoing need for reliable, validated methods tailored to this unique population. Until improved approaches are widely accessible, serum creatinine remains the most practical—albeit imperfect—marker guiding clinical decision-making in cirrhotic patients.

Abstract Improved understanding of how chimeric antigen receptor (CAR) and endogenous T‐cell phenotypes associate with progression‐free survival (PFS) is needed to individualize and improve immunotherapy outcomes in multiple myeloma (MM). We characterized and investigated the prognostic value of immune dynamics defined with multidimensional and computational flow cytometry in 258 bone marrow aspirates from 107 MM patients treated with idecabtagene vicleucel in the KarMMa trial. At screening, there was an association between longer PFS and increased percentages of PD1 + cytotoxic T cells and ICOS − TIGIT + Tregs. At Month 1 after infusion, the presence of >1% CAR‐T cells, a CD4/CD8 CAR‐T‐cell ratio >0.09, and greater abundance of non‐activated non‐cytolytic CAR‐T cells identified patients with longer PFS. Notably, 47 of the 115 endogenous T‐cell clusters were prognostic at the latest assessment performed after CAR‐T infusion. Lower percentages of ICOS + TIGIT − Tregs showed the strongest association with longer PFS. Altogether, this large dataset of dynamic immune profiling throughout treatment with anti‐B‐cell maturation antigen (anti‐BCMA) CAR‐T cells uncovered that the T‐cell composition prior to apheresis as well as CAR‐T and endogenous T‐cell phenotypes after infusion associates with PFS. These findings have potential for translation into routine laboratory practice for improved understanding of response and resistance to CAR‐T cells in relapsed/refractory MM.

Abstract Objective The upper frequency limit of human brain activity remains unknown. Using ultrahigh sampling rate (≥20 kHz) intracranial microelectroencephalography, this study aimed to systematically explore and quantitatively characterize brain field oscillations beyond the established high‐frequency oscillation range (>2 kHz), and to determine their relationship to epileptogenic tissue. Methods We analyzed intracranial electroencephalographic recordings from 15 patients with drug‐resistant epilepsy, comprising 466 microcontacts and 434 macrocontacts implanted in mesiotemporal structures across four international epilepsy centers. A custom spectrogram‐based detector optimized for ultrahigh frequencies was developed to identify ultrafast oscillations (UFOs; >2 kHz). UFO rates were assessed in epileptic (successfully resected) and nonepileptic hippocampi and compared with established electrophysiological biomarkers, including interictal epileptiform discharges, ripples, and fast ripples. Statistical comparisons were performed using mixed‐effects models to account for intersubject and interelectrode variability. Results We identified a previously undescribed class of short‐duration oscillatory events spanning 2–8 kHz. UFOs occurred at significantly higher rates in epileptic compared with nonepileptic mesiotemporal regions, with the strongest differentiation observed in the 2–3‐kHz band. Two distinct UFO phenotypes were consistently observed: (1) spindlelike, narrow‐band oscillations and (2) sharp‐onset, rapidly decaying bursts. Both forms were prevalent within epileptic hippocampi but were exceedingly rare in nonepileptic structures. UFOs exhibited pronounced temporal intermittency and spatial focality and frequently arose independently of ripples, fast ripples, and very high‐frequency oscillations, indicating that they represent a distinct electrophysiological phenomenon. Macrocontacts detected UFOs only exceptionally, highlighting the necessity of microelectrode recordings to capture activity in this ultrahigh‐frequency regime. Significance These findings substantially extend the known frequency range of human brain field activity and identify ultrafast oscillations as a novel biomarker of neuronal hyperexcitability. UFOs likely reflect pathological microcircuit dynamics inaccessible to conventional clinical recordings and provide new insights into the organization and pathophysiology of epileptogenic networks.

ABSTRACT Background & Aims Metabolic dysfunction‐associated steatotic liver disease (MASLD) is highly prevalent and increasingly recognized as a multisystem cardiometabolic disorder. The global burden, incidence and prognostic implications of coexisting chronic kidney disease (CKD) in MASLD remain uncertain. Methods In this meta‐analysis, we searched MEDLINE and EMBASE from inception through September 25, 2025, for observational studies reporting CKD prevalence and/or incidence among adults (≥ 18 years) with MASLD. The primary outcomes were pooled CKD prevalence, estimated using random‐effects models on the logit scale with the Hartung–Knapp adjustment, and pooled CKD incidence (per 1000 person‐years), estimated using random‐effects models with exact Poisson confidence intervals. Secondary outcomes included all‐cause mortality and cardiovascular, renal and cancer outcomes. Results From 2811 records, 36 observational studies met the inclusion criteria. Twenty‐three studies contributed prevalence estimates (575 615 participants; 56 248 CKD cases) and thirteen studies contributed incidence estimates (27 996 new events). The pooled global CKD prevalence among individuals with MASLD was 15.22% (95% CI 9.69–23.12). The pooled CKD incidence was 22.17 per 1000 person‐years (95% CI 11.44–32.89) in the MASLD population. Hypertension (OR 1.49, 95% CI 1.29–1.72), dyslipidaemia (OR 1.22, 95% CI 1.20–1.24) and diabetes (OR 1.94, 95% CI 1.69–2.22) were associated with higher odds of CKD in the MASLD population. All‐cause mortality rates were 18.28 per 1000 person‐years (95% CI 3.45–33.11) in coexistent MASLD and CKD, more than double those in the MASLD‐only population (7.26 per 1000 person‐years (95% CI 2.97–11.56)). Conclusions Coexistent CKD affects one in seven individuals with MASLD worldwide, conferring a more than two‐fold increased risk of all‐cause mortality compared with individuals with MASLD alone.

Abstract Recent single-cell transcriptomic studies of follicular lymphoma (FL) have revealed heterogeneity among malignant B (MB) cells and selected components of the tumor microenvironment (TME), but have been constrained by relatively small sample sizes and a lack of spatial context. We performed comprehensive cellular profiling and spatial dissection of over five million cells by integrating single-nucleus RNA sequencing (snRNA-seq) from 182 samples (FL, n = 167; control, n = 15) with single-cell spatial transcriptomics (ST) from 386 samples (FL, n = 365; control, n = 21). After stringent quality control, 1,289,073 and 3,968,427 cells from snRNA-seq and ST data, respectively, were analyzed. Unsupervised clustering of snRNA-seq data identified 58 TME cell subtypes. To extend this classification to the ST dataset, we integrated snRNA-seq and ST data by co-embedding them into a shared principal component space, enabling robust batch correction and cell-type label transfer across modalities. Using this supervised annotation framework, ST data recapitulated 54 TME cell subtypes. MB, proliferating MB (MBprolif), and healthy B (HB) cells were classified using sample-level unsupervised clustering in ST. Macrophages exhibited previously uncharacterized heterogeneity in transcriptomic profiles and spatial distribution. We identified CXCL13-expressing macrophage subtypes with high intra- and peri-follicular abundance, termed follicular macrophages (FMs). Non-negative matrix factorization of intrafollicular cell fractions identified five TME archetypes: FM, follicular stroma, two follicular T, and HB archetypes. The FM archetype was enriched for intrafollicular macrophages, including FMs, and showed a significantly higher proportion of grade 3A/3B cases (53.4%) compared to other archetypes (≤16.5%). It was also associated with a higher frequency of high tumor burden requiring treatment initiation rather than a watch-and-wait (WW) approach. Among patients managed by WW, those with the FM archetype showed significantly shorter event-free survival (EFS) compared to those with non-FM archetypes, whereas this association was not observed among treated patients. The percentage of intrafollicular macrophages (IFMP) showed excellent predictive performance for the FM archetype (area under the curve: 0.90). IFMP calculated in a published multiplex spatial protein imaging dataset from an independent cohort of 242 FL patients validated the associations between high IFMP and both pathology grade 3A/3B and shorter EFS in WW patients. Consistently, spatial neighborhood and cell–cell communication analyses revealed co-localization of FMs and MBprolif cells, forming a distinct niche with activated signaling mediated by FM-derived CXCL13, APRIL, and BAFF. Our integrative multi-modal analysis defines previously unrecognized cellular heterogeneity and spatial architecture in FL and highlights macrophage-enriched follicular ecosystems associated with aggressive clinicopathological features, providing a framework for improved biological understanding and patient management. Citation Format: Yoshiaki Abe, Bijal Thakkar, Atish Kizhakeyil, Ashley Wilson, Andrew L. Feldman, Jared Henderson, Amy Ayers, Sara Borgschatz, R. Andrew Harkins, Priya Lakra, Daisuke Kaji, Jonathon B. Cohen, David Russler-Germain, Eric Mou, Francisco Vega, Jennifer Chapman, Giorgio Inghirami, Carla Casulo, Izidore S. Lossos, Jean L. Koff, Chijioke Nze, Peter Martin, Sergei Syrbu, Kiran Vij, David L. Jaye, James R. Cerhan, Christopher R. Flowers, Anne J. Novak, Richard Burack, Dai Chihara, Mamiko Sakata-Yanagimoto, Joshua Tobin, Xubin Li, Michael R. Green. Spatially resolved microenvironment profiling reveals distinct follicular lymphoma archetypes [abstract]. In: Proceedings of the Fifth AACR International Meeting on Advances in Malignant Lymphoma: From Discovery to Clinical Impact; 2026 Jun 24-27; Philadelphia, PA. Philadelphia (PA): AACR; Blood Cancer Discov 2026;7(3_Suppl):Abstract nr A049.

Importance Clinical trials in cardiovascular medicine aim to deliver high-quality evidence with greater efficiency, including smaller sample sizes and shorter timelines. The selection of sensitive and reliable end points is central to this goal. Right ventricular (RV) structure and function play a critical role in many cardiovascular conditions; however, RV-specific parameters remain underused and inconsistently applied in interventional clinical trials. In this article, the current and emerging role of RV-focused imaging and hemodynamic parameters as end points in clinical trials are explored and a comprehensive framework for their development, validation, and broader implementation is proposed. Observations Across multiple disease domains, RV-focused parameters derived from echocardiography, cardiac magnetic resonance imaging, computed tomography, and right-sided heart catheterization demonstrate potential value in assessing the therapeutic effects of new medicines or devices across a wide range of conditions including heart failure, cardiomyopathies, valve diseases, pulmonary hypertension, and congenital heart conditions. However, their use is inconsistent, and feasibility challenges are common, particularly in multicenter clinical trial settings. Key limitations include variability in imaging acquisition, incomplete data capture, lack of standardized protocols, and insufficient validation linking short-term RV changes to long-term clinical outcomes. Emerging tools such as artificial intelligence may improve reproducibility and efficiency, while collaborative, multidisciplinary efforts are essential for advancing end-point development. Conclusions and Relevance RV-specific end points hold substantial promise for enhancing the sensitivity and mechanistic insight of clinical trials but remain inadequately integrated into current practice. Optimal end-point selection requires balancing clinical relevance, analytical validity, and operational feasibility, with consideration of disease-specific pathophysiology and trial design. Standardization of acquisition, validation of clinically meaningful changes, and centralized data analysis are important next steps. Broader adoption of robust RV metrics supported by technological innovation and cross-sector collaboration has the potential to improve trial efficiency, accelerate therapeutic development, and ultimately enhance patient outcomes.

Abstract Background Oligodendrogliomas were previously defined by histology, but since 2016, the WHO has integrated molecular signatures to create the entity of IDH-mutant 1p/19q-codeleted oligodendroglioma. These tumors harbor recurrent genetic alterations—including IDH mutations, CIC and FUBP1 loss-of-function mutations, and PI3K-activating mutations—that collectively define a genetic profile distinct from IDH-mutant astrocytoma and IDH wild-type glioblastoma. The paucity of faithful model systems has impeded progress in advancing mechanistic insights and therapeutic development for oligodendroglioma. Results To test whether recurrent mutations found in oligodendroglioma patients would drive tumor formation in mice, we utilized in utero electroporation to introduce combinations of gain- and loss-of-function mutations into the developing cortex. Initial tests that included expression of IDH-and PIK3CA-mutants with Cic and Fubp1 loss (termed Oligo) were non-tumorigenic but biased cells towards glial lineages. Introducing Cdkn2a-loss, which is normally suppressed by IDH-associated epigenetic changes in human tumors, to the Oligo combination (termed Oligo-Cdkn2a) resulted in fully penetrant tumor formation. Histopathological review showed the Oligo Cdkn2a-loss mouse model resembled grade II/III oligodendroglioma with rounded nuclei and open chromatin. If Trp53-loss is used (termed Oligo-Trp53) in place of Cdkn2a-loss, tumor histology shifts to a more astrocytic phenotype with angulated nuclei with denser chromatin, demonstrating a direct impact of Trp53-loss on histological features. Bulk RNA-sequencing verifies metabolic alterations driven by the presence of IDH-mutations in Oligo-Cdkn2a mouse models compared to an IDH wild-type GBM model. Single-cell transcriptional profiling shows that Oligo-Cdkn2a tumors contain an increased population of tumor cells that resemble more differentiated oligodendrocytes. Examination of the tumor immune microenvironment within Oligo-Cdkn2a and IDHWT GBM mouse models is being performed to determine changes in immune cell infiltration and transcriptional programs. Conclusion We have created, to our knowledge, the first murine model of IDH-mutant 1p/19q-codeleted oligodendroglioma that incorporates Cic loss. This immune-competent mouse model of IDH-mutant 1p/19q-codeleted oligodendroglioma offers a powerful new tool for interrogating tumor biology and evaluating preclinical therapeutic strategies.

Abstract Background Approximately 12,000 adolescents and young adults (ages 15-39, AYAs) are diagnosed with a primary central nervous system (CNS) tumor each year. DNA methylation profiling has transformed CNS tumor classification by refining diagnostic accuracy and identifying biologically distinct subtypes, but its application has not been systematically evaluated in the AYA population. In this study, we examined the spectrum of CNS tumor types across age groups, with a focus on the AYA population. Methods We assembled a large dataset of CNS tumor samples with age annotations and methylation profiles matching with high confidence to a CNS tumor type using the NCI/Bethesda classifier. Prevalence of tumor type, methylation class and DNA copy number aberrations were compared across age strata (pediatric, AYA and adult). Results The cohort of 21,099 CNS tumors included 5139 tumors from AYAs (24%), which showed a mixed pattern, with tumors typical of childhood (e.g. medulloblastoma) as well as those common in older adults (e.g. glioblastoma). Several tumor types were specifically enriched in the AYA, including IDH-mutant astrocytoma, pleomorphic xanthoastrocytoma, posterior fossa group B ependymoma, and diffuse hemispheric glioma, H3 G34-mutant, among others. Distinct methylation subclasses of multiple tumor types were observed in the AYA, and patterns of genomic aberrations showed age-specific distributions. Conclusion Large-scale methylation profiling revealed unique classification patterns of CNS tumors in AYAs, with specific tumor types, subclasses, and genomic alterations enriched in this population. These data may serve as a valuable reference resource for better understanding the spectrum of CNS tumors affecting AYA patients.