Citations

Abstract Hepatic spheroids are widely used in bioartificial liver (BAL) systems, hepatotoxicology, and pharmacology due to improved functional stability compared with monolayer cultures. However, many existing methods rely on specialized equipment or static platforms that limit scalability and dynamic culture applications. Primary rat hepatocytes were cultured as three‐dimensional spheroids using a rocker‐based suspension system. Spheroid formation was evaluated across a range of rocking speeds (7–18 cycles per minute [cpm]) and inoculation densities. Spheroid morphology was quantified over time using two‐dimensional imaging. Functional performance was assessed by urea and albumin production on days 1, 4, 7, and 10. Spheroid formation efficiency was evaluated using volumetric modeling. Mean spheroid diameter decreased from 199 ± 41 μm at 7 cpm to 80.2 ± 17.6 μm at 18 cpm. The spheroid area was significantly influenced by both culture day ( p < 0.0001) and rocker speed, with significant differences observed across speeds at all time points ( p < 0.001, days 1–7). Mean spheroid area at 10 cpm was 13,750 ± 9051 μm 2 (day 1), 26,730 ± 8658 μm 2 (day 4), and decreased to 22,526 ± 8705 μm 2 (day 7). Urea production differed across speeds (ANOVA, p = 0.043), with peak performance at 12 cpm (median 3.47 μg/μg DNA) compared to 7 cpm (median 0.11 μg/μg DNA). Albumin production was 1086.8 ng/μg DNA on day 1 and 1534.4 ng/μg DNA on day 10. Urea production was 0.62 μg/μg DNA on day 1 and 1.25 μg/μg DNA on day 10. Median hepatocyte incorporation was 86% (range 73%–116%) by day 4. This rocker‐based method provides a simple, low‐cost, and scalable approach for generating hepatic spheroids with tunable size distributions under dynamic conditions. The system supports progressive functional maturation and is compatible with established scale‐up strategies, supporting its potential for translational applications.

Abstract Exposure to asbestos is the primary cause of mesothelioma, however the processes underpinning its initiation and evolutionary trajectory remain elusive. To address this knowledge gap, we conducted whole exome sequencing and phylogenetic analysis of 277 mesotheliomas. Using multidimensional Dirichlet process clustering we inferred phylogenies, uncovering mutation order dominated by early 13q,1p, 8p, 6q and 22q somatic copy number alterations. Mesotheliomas exhibit a spectrum of genomic intra-tumor heterogeneity spanning linear (L) to highly branched (B) tree topologies, quantifiable by the Weighted Shannon Entropy (WSE). Somatic copy number alterations emerge earlier than single nucleotide variants (SNVs), and at a much faster relative rate in L-mesotheliomas. BAP1 is the only positively selected driver in L-mesotheliomas, whereas, B-mesotheliomas harbor multiple positively selected drivers and an aggressive phenotype, including a bias of loss of RPL5, and MTAP deletion linked to breakpoint enriched with long interspersed nuclear elements. L-trees had lower WSE, but greater T-cell inflammation and tertiary lymphoid structures, despite having a lower neoantigen burden. WSE is higher in larger volume, immunologically cold mesotheliomas, and is associated with shorter survival. In summary, progressive genomic heterogeneity is a defining feature of more aggressive mesothelioma yet illuminates opportunities for precision therapeutic intervention.

Prehabilitation with Impella 5.5 offers hemodynamic support while allowing early mobilization, yet its overall effect on post-transplant recovery remains unclear. The aim was to assess recovery during Impella 5.5–supported prehabilitation and determine its association with early post-heart transplant outcomes, including a potential dose–response relationship with ambulatory activity. We conducted a single-center retrospective cohort study of adults bridged to transplant with Impella 5.5 between April 1, 2022 and September 30, 2024. Daily walking distance, recorded by nursing staff, served as the intervention. Primary outcome was postoperative hospital length of stay (LOS); the secondary outcome was time to extubation. Fine–Gray competing-risk models, adjusted for age, Sequential Organ Failure Assessment (SOFA) score, New York Heart Association (NYHA) class, and days of Impella support, assessed associations. Longitudinal recovery trajectories were analyzed with linear mixed-effects models incorporating restricted cubic splines. Among 82 eligible patients, 65 met the inclusion criteria. Patients who walked farther during Impella 5.5 support in the intensive care unit (ICU) had shorter hospital stays and were taken off the ventilator sooner after transplantation. The overall recovery peaked during the first 2–3 weeks of support, with smaller recovery thereafter, indicating that most functional recovery occurred early during prehabilitation.

ABSTRACT One quarter of patients with diffuse large B‐cell lymphoma (DLBCL) who achieve a complete response following front‐line therapy will eventually experience disease relapse. Existing prognostic models use baseline factors to predict outcomes from the start of initial therapy and are not intended for use following completion of treatment. We developed a conditional event‐free survival (cEFS) tool that predicts a patient's risk of lymphoma recurrence after completing front‐line therapy taking into consideration baseline risk characteristics plus the time the patient has been in remission. Model development used pooled and harmonized data from two observational cohorts and four randomized trials of patients with newly diagnosed DLBCL treated with immunochemotherapy and either achieving a complete response or not experiencing an event within 12 weeks of end of therapy. Cox proportional‐hazards regression modeling with backwards stepwise selection was utilized for model development. External validation was performed using a large independent data registry. In total, data from 2757 patients were used for model development. The risk of experiencing an event at a time point after having survived a period of time could be computed parsimoniously using four basic predictors: age, ECOG performance status grade, Ann Arbor stage, and lactate dehydrogenase level. C‐index in the model development cohort was 0.65 (95% CI, 0.63–0.68), compared to 0.64 (95% CI, 0.62–0.66) in the external validation cohort. We believe that this dynamic risk prediction tool will not only aid clinicians in providing data‐driven recommendations for surveillance, but also assist patients themselves with key decisions, such as family planning.

Background Tumor-infiltrating lymphocytes (TILs) are established determinants of clinical outcomes in breast cancer. 1–6 While stromal TILs (sTILs) are commonly evaluated due to easier scoring and higher interobserver reproducibility, intraepithelial TILs may provide additional insights into anti-tumor immunity. 7 We aimed to comprehensively characterize immunotype-associated cellular landscapes in triple-negative breast cancer (TNBC) and identify features associated with clinical outcomes. Methods 212 TNBC tumors were classified into three immunotypes based on immune infiltrate location and density: immune desert (ID), immune excluded (IE), and immune inflamed (IN). 8 Single-cell spatial transcriptomics was performed on 75 tumors to define the cellular composition and functional states of the tumor microenvironment across immunotypes. Findings were validated and integrated with bulk RNA sequencing data and clinical outcome datasets from FinXX, CALGB-40603, I-SPY 2, and Real-World Clinico-Genomic Data (RWCGD) cohorts. Results Patients with IN tumors had significantly improved outcomes compared with ID tumors. Despite high sTILs, IE tumors showed poor outcomes similar to ID tumors. Single-cell spatial analysis revealed that ID and IE tumors exhibited reduced major histocompatibility complex I/II expression and fewer tumor-resident plasmacytoid dendritic cells (pDCs) compared with IN tumors, which were enriched for interferon-alpha (IFNα) and interferon-gamma (IFNγ) responses. High IFN response scores were associated with favorable outcomes across multiple therapy types in independent datasets. Deconvolution of RWCGD bulk RNA-seq data confirmed that pDC abundance correlated with improved outcomes specifically in hormone receptor–negative subtypes. Conclusions Our study highlights pDCs and IFN signaling as hallmarks of effective anti-tumor immunity in TNBC. Immunotype-based profiling underscores the limited prognostic value of sTILs alone in immune-excluded tumors and supports pDCs and IFN pathways as potential biomarkers for prognosis and therapeutic development in TNBC.