Citations

Abstract The liver is organized into tightly regulated zones with distinct metabolic functions but zonation erodes with age. Cellular senescence contributes to aging and liver diseases, however, its impact on aging biology is ill-defined. As part of The Cellular Senescence Network Consortium, we used multiple spatial transcriptomics approaches (GeoMx, Visium, CosMx) with snRNA-seq to profile senescence signatures, zonation markers, and metabolic pathways in livers from wild-type (WT) mice of multiple ages. We observed a loss of canonical zone signatures in aged mouse livers characterized by “expansion” of midlobular (zone 2) marker gene expression, accompanied by diminished expression of zone 3 marker genes by middle-age (18 months), indicative of loss of cell identity. Multiple analytic approaches identified distinct age-, zone- and sex-specific senescence signatures, which were significantly associated with zonation markers changes. This was recapitulated in Ercc1 mutant models of accelerated senescence, supporting a causal role of senescent cells in liver aging. A “no-zone” hepatocyte-like cluster expanded with age and with the strongest Senescence-Associated Secretory Phenotype (SASP) profile. Gene expression profiles from senescent hepatocytes implicate decreased WNT signaling and increased BMP as contributing to age-related loss of zonation. Together, these data elucidate the role of senescent cells in driving aging biology in non-diseased liver through disruption of cell:cell signaling and the loss of metabolic and cell identity gene expression necessary for hepatocyte function.

Vascular stents are crucial devices in the treatment of cardiovascular diseases, and their structural design and function critically affect therapeutic efficacy and patient prognosis. Conventional stents can effectively restore vascular patency by providing mechanical support to blood vessels. However, they still face significant challenges including restenosis, thrombosis, and limited adaptability to complex patient-specific lesion characteristics. To address these limitations, drug delivery offers an important strategy to modulate the pathological microenvironment, enhance long-term vascular healing, and reduce systemic side effects. Meanwhile, advances in computational simulations have provided powerful tools for optimizing stent design through structural mechanics, hemodynamics, and drug release modeling. Computational approaches enable the rational design of stent architectures with improved mechanical stability, vascular compatibility, and therapeutic regulation. Consequently, the development of vascular stents is evolving toward the synergistic integration of drug delivery, structural optimization, and intelligent design. This review summarizes the latest advances in functional vascular stents, clinical applications and computational design. This work aims to provide valuable insights for the engineering of efficient, precise, and intelligent vascular stents for cardiovascular therapies.

ABSTRACT Background Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive cyst growth, inflammation, fibrosis, and renal failure. Klotho is a renoprotective protein with antiproliferative, anti-inflammatory, and antioxidant properties, but its mechanistic role in ADPKD remains poorly defined. Methods Klotho expression was analyzed in human ADPKD kidneys, public bulk and single-cell RNA sequencing datasets, Pkd1 mutant renal epithelial cells, and Pkd1 mouse models. The therapeutic effects of recombinant Klotho were evaluated in late-onset Pkd1fl/fl:tamoxifen-Cre mice. Molecular mechanisms were investigated using cell viability assays, western blotting, reverse transcription quantitative polymerase chain reaction (RT-qPCR), immunohistochemistry, ferroptosis assays, DNA methylation analysis, and chromatin immunoprecipitation assay. Results Klotho expression was markedly reduced in human ADPKD kidneys and Pkd1-deficient cells and mice, particularly in distal nephron segments. Recombinant Klotho treatment significantly reduced cyst burden, kidney enlargement, and blood urea nitrogen levels, while decreasing epithelial proliferation and increasing apoptosis in cyst-lining cells. Mechanistically, Klotho suppressed PKD-associated signaling pathways, including protein kinase B (AKT), signal transducer and activator of transcription 3 (STAT3), and retinoblastoma protein (Rb), reduced nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB)-mediated inflammation via downregulation of Smyd2, and attenuated transforming growth factor-beta (TGF-β)-Smad-dependent renal fibrosis. Klotho also inhibited ferroptosis by upregulating GPX-4 and reducing lipid peroxidation. Epigenetic analyses revealed DNA methyltransferase 1 (DNMT1)-mediated hypermethylation of the Klotho promoter and gene body in ADPKD kidneys, contributing to Klotho silencing. Inhibition of DNMT1 restored Klotho expression, and recombinant Klotho reduced DNMT1 levels, suggesting a negative feedback loop. Conclusions Klotho is epigenetically repressed in ADPKD and functions as a central regulator of cyst growth, inflammation, fibrosis, and ferroptosis. Restoration of Klotho signaling markedly attenuates disease progression in Pkd1 mutant mice, identifying the Klotho–DNMT1 axis as a promising therapeutic target for ADPKD.

Abstract Purpose: Standard care for high-grade gliomas (HGG) involves maximal surgical resection followed by radiation and temozolomide. Postoperative adjuvant therapy frequently causes lymphopenia, which is associated with poor prognosis. Interleukin 7 (IL7) is essential for lymphocyte development, homeostasis, and survival. NT-I7 (efineptakin alfa), a long-acting recombinant IL7, reverses lymphopenia and improves survival in murine glioma models. However, the safety, maximum tolerated dose (MTD), and impact of NT-I7 on immune cells in patients with HGG remain unknown. Patients and Methods: We conducted a phase I trial (NCT03687957) examining the MTD and effect of NT-I7 on lymphocytes in patients with newly diagnosed HGG. The primary endpoint was dose-limiting toxicity; secondary endpoints included absolute lymphocyte count (ALC) changes over time, overall response, progression-free survival, and overall survival. Exploratory endpoints included immune profiling at different time points using single-cell RNA sequencing (scRNA-seq) in a subset of patients. Results: NT-I7 was well tolerated with a MTD of 720 µg/kg. Moreover, NT-I7 significantly increased ALCs for more than 12 weeks in duration. Early elevations in CD4+, CD8+ T cells and NK cells further coincided with increased TNF and CXCL9 cytokine levels. Comprehensive immune profiling of peripheral blood T cells revealed selective clonotype expansion within CD8+, but not CD4+, T cells following NT-I7 administration. Finally, a subset of our patients with MGMT promoter–unmethylated glioblastoma, which are typically associated with a poorer prognosis, demonstrated promising clinical responses. Conclusions: NT-I7 has the potential to maintain and increase lymphocyte counts in patients with HGG and warrants further investigation, particularly in combination with immune-based therapies.

Abstract Introduction: Graft Failure (GF) is a rare but devastating outcome of HCT. Primary GF (PGF), defined as a failure of neutrophil recovery by Day+28, is straightforward to diagnose. Diagnosing secondary GF (SGF) is more challenging, with its broad time-range, multiple confounding diagnoses, and lack of predictive biomarkers. In BMT CTN1703/1801, we analyzed patients receiving RIC HCT for heme malignancies with either Tac/MTX (n=159) or PT-Cy (n=165) GVHD prophylaxis. SGF was defined as donor chimerism <5% after initial donor engraftment. With Tac/MTX, there were 3 PGF and 1 SGF diagnoses. With PT-Cy, there were 4 PGF and 6 SGF. Median SGF diagnosis was Day +64 (range: Day+28-215). There were too few Tac/MTX patients to analyze SGF, but sufficient events with PT-Cy. To identify PT-Cy SGF predictors, we leveraged lymphocyte, T, B, and NK cell reconstitution analysis. In SGF we found an early, profound deficit in the reconstitution of all major lymphocyte populations, including total lymphocytes, T, B, and NK cells, as early as Day+28. This enabled the modeling of a SGF risk classifier based on the Absolute Lymphocyte Count (ALC). Methods: Clinical ALC measurements were performed on all SGF patients (n=6) and on non-GF controls with ALCs available (146 of 155 non-GF patients). Flow cytometry was performed on all PT-Cy SGF patients (n = 6) and from a subset of non-GF controls (n = 18: controls were chosen as patients without relapse or severe GVHD, to reduce confounders introduced by immunologic interventions, and for whom all samples, including from the graft infusion, were available). T, B, and NK counts, as well as T cell subsets, were compared (using Welch's T test) on Days 7, 14, 21, 28, 42, 63, 98, 180, 270, 365, 730, with SGF patients censored on the day of GF diagnosis. To interrogate the optimal ALC cutoff, the cumulative incidence of SGF was computed at Days +28 and +42, with death without GF as a competing risk. Results: We have previously demonstrated that, compared to Tac/MTX, PT-Cy patients exhibited an early decrease in reconstitution of all T cell populations (with normal NK and B cell reconstitution). Here we focused specifically on PT-Cy patients with or without SGF. Graft CD34 counts/kg were not different between SGF patients and non-GF patients (mean CD34/kg = 1.38 x10e6 (SGF) vs 0.67 x10e6 (non-GF, p = 0.61) However, even amidst the overarching early suppression in T cell reconstitution with PT-Cy, SGF patients could be easily distinguished from the larger PT-Cy cohort, based on more profound deficits in ALC, T, B and NK cells reconstitution, measured using 2 strategies: (1) SGF patients demonstrated significant early (Day +28) quantitative defects in the reconstitution of the ALC (mean +/- SEM 262+/-32 cells/µL (non-GF) vs 60 +/- 25 (SGF, p<0.0001), CD4 T cells (62 +/- 12 cells/µL vs 19+/-15, p=0.048), CD8 T cells (15 +/-3 cells/µL vs 3.5 +/-1 p=0.0009), all CD8 T cell subpopulations, as well as NK cells (116+/-31 cells/µL vs 2.9+/-1.4 cells/µL, p= 0.002) and B cells (3.5 +/-1.4 cells/µL vs 0.16+/-0.07 p =0.03). (2) In SGF, there was a significant deficit in the rate of rise of all major lymphocyte populations between Days 28-42-60 vs non-GF, including CD4 T cells (p<0.0001), CD8 T cells (p = 0.0002), B cells (p<0.0001), and NK cells (p =0.048). These discoveries suggested that a classifier could be identified to risk-stratify patients for SGF. We explored an ALC cutpoint, amenable to standard clinical lab analysis. A statistically significant threshold was identified at both Days+28 and +42, with Day+42 being most predictive: A threshold of 120 cells/µL was identified as optimal, with landmark analysis documenting a SGF rate of 34.7% below the cutpoint, and SGF of 1% above it (HR = 45.9, 95% CI 5.7 - 366). Conclusions: Despite the small number of events, PT-Cy patients with SGF demonstrated a distinctive reconstitution trajectory that encompassed an early, substantial, and sustained deficit in all lymphocyte counts, as well as a lack of their longitudinal expansion. This enabled the discovery of a candidate ALC biomarker cutpoint at Day+42 that could distinguish patients who were more likely to develop SGF. If confirmed, these data could generate a predictive biomarker for SGF, which would enable the design of trials evaluating early interventions (e.g. CD34+ boosts, DLI, modification of immunosuppression) to improve outcomes for these patients.

ABSTRACT Introduction Publication bias (PB) threatens the validity of meta‐analyses by distorting effect size estimates, potentially leading to misleading conclusions. With advanced pattern recognition and multimodal capabilities, large language models (LLMs) may be able to evaluate PB and make the systematic review process more efficient. Methods We evaluated the ability of two state‐of‐the‐art multimodal LLMs, GPT‐4o and Llama 3.2 Vision, to detect PB using funnel plots alone and in combination with quantitative inputs. We simulated meta‐analyses under varying conditions, including the absence of PB, different levels of presence of PB, varying total number of studies within a meta‐analysis, and differing degrees of between‐study heterogeneity. Results Neither GPT‐4o nor Llama 3.2 Vision consistently detected the presence of PB across various settings. Under no‐publication‐bias conditions, GPT‐4o achieved a higher specificity outperforming Llama 3.2 Vision, with the difference most shown in the meta‐analyses with 20 or more studies. The inclusion of quantitative inputs alongside funnel plots did not significantly improve performance. Additionally, between‐study heterogeneity and patterns of non‐reported studies had minimal impact on the models’ assessments. Conclusions The ability of LLMs to detect PB without fine‐tuning is limited at the present time. This study highlights the need for specialized model adaptation before LLMs can be effectively integrated into meta‐analysis workflows. Future research can focus on targeted refinements to enhance LLM performance and utility in evidence synthesis.

Abstract Current discussion surrounding the clinical capabilities of generative language models (GLMs) predominantly center around multiple-choice question-answer (MCQA) benchmarks derived from clinical licensing examinations. While accepted for human examinees, characteristics unique to GLMs bring into question the validity of such benchmarks. Here, we validate four benchmarks using eight GLMs, ablating for parameter size and reasoning capabilities, validating via prompt permutation three key assumptions that underpin the generalizability of MCQA-based assessments: that knowledge is applied, not memorized, that semantic consistency will lead to consistent answers, and that situations with no answers can be recognized. While large models are more resilient to our perturbations compared to small models, we globally invalidate these assumptions, with implications for reasoning models. Additionally, despite retaining the knowledge, small models are prone to answer memorization. All models exhibit significant failure in null-answer scenarios. We then suggest several adaptations for more robust benchmark designs more reflective of real-world conditions.