Citations

Introduction Uveal melanoma has a marked tropism for the liver where immune tolerance facilitates metastatic progression and resistance to immunotherapy. Impaired CD8 + T cell immunosurveillance is a central determinant of disease progression in uveal melanoma, yet the underlying mechanisms driving liver-mediated immune subpression and hepatic metastasis are not fully understood. Here, we investigate molecular pathways that regulated hepatic CD8 + T cell function and evaluate clinical outcomes associated with liver-directed therapy. Methods Expression of autotaxin (ATX), the expression responsible for generating lysophosphatidic acid (LPA), was evaluated in hepatic resident cell populations. ATX transcript levels were assessed in CD8 + T cells isolated from hepatic metastases and compared with matched peripheral blood and healthy donor control. Antigen-specific effector CD8 + T cells were used to characterize downstream signaling responses to LPA stimulation. Functional studies evaluating cytokine production during chronic antigen exposure were performed using CD8 + T cells from LPA receptor 5-deficient ( Lpar5 -/- ) mice. Results We identify the autotaxin-lysophosphatidic acid (ATX-LPA) axis as a prominent immunoregulatory pathway in the metastatic hepatic tumor microenvironment. ATX, the enzyme responsible for LPA production, is constitutively expressed by hepatic resident cells, is detectable on Kupffer cells and is associated with increased immunosubpressive markers. CD8 + T cells isolated from hepatic metastasis in a patient with uveal melanoma display markedly elevated ATX transcripts compared to matched peripheral blood (>5 log 2 fold change) and healthy controls. Using antigen-specific effector CD8 + T cells, we demonstrate LPA signaling induces low level, persistent ERK phosphorylation distinct from canonical antigen-induced TCR signaling. Genetic deletion of the LPA receptor 5 ( Lpar5 -/- ) on CD8 + T cells restores CD8 T cell percentages and cytokine function during persistent antigen stimulation in the presence of LPA. Discussion These findings define an ATX-LPA mechanisms of dysfunctional ERK signaling that may contribute to hepatic immune subpression in uveal melanoma. We highlight this pathway as a rational therapeutic target alongside liver-directed clinical interventions.

ABSTRACT Overview Systemic mastocytosis (SM) results from clonal proliferation of mast cells (MC) in extra‐cutaneous organs. Diagnosis The major criterion is the presence of multifocal MC clusters in the bone marrow and/or extracutaneous organs. Minor diagnostic criteria include elevated serum tryptase level, MC CD25/CD2/CD30 expression, and the presence of activating KIT mutations. Risk Stratification Establishing SM subtype as per the International Consensus Classification/World Health Organization classification systems is an important first step. Patients either have indolent/smoldering SM (ISM/SSM) or advanced SM, including aggressive SM (ASM), SM with associated myeloid neoplasm (SM‐AMN), or mast cell leukemia. Identification of poor‐risk mutations (i.e., ASXL1, RUNX1, SRSF2, NRAS ) further refines the risk stratification. Several risk models are available to help assign prognosis in SM patients. Management Treatment goals for ISM patients are primarily directed towards anaphylaxis prevention/symptom control/osteoporosis treatment. Patients with advanced SM frequently need MC cytoreductive therapy to reverse disease‐related organ dysfunction. Tyrosine kinase inhibitors (TKI) (midostaurin, avapritinib) have changed the treatment landscape in SM. While deep biochemical, histological, and molecular responses have been documented with avapritinib treatment, its efficacy as monotherapy against a multimutated AMN disease component in SM‐AMN patients remains unclear. Cladribine continues to have a role for MC debulking, whereas interferon‐α has a diminishing role in the TKI era. Treatment of SM‐AMN primarily targets the AMN component, particularly if an aggressive disease such as acute leukemia is present. Allogeneic stem cell transplant has a role in such patients. Imatinib has a therapeutic role only in the rare patient with an imatinib‐sensitive KIT mutation.

Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) recently celebrated its 20th anniversary, reflecting two decades of major contributions to Alzheimer's research through open data sharing and longitudinal multimodal assessments. This review synthesizes 122 high‐impact studies using ADNI data or biospecimens from 2023 to mid‐2025 to clarify mechanisms of Alzheimer's disease (AD) progression. Studies describe impairment of glymphatic clearance and the impact of cerebral small vessel disease, trajectories of amyloid beta and tau deposition, inflammation, metabolic disturbances, synaptic dysfunction, and neurodegeneration, leading to cognitive impairment and neuropsychiatric symptoms. Multifactorial contributions from genetic and epigenetic influences, co‐pathologies and comorbidities, and mechanisms of resilience modulate disease progression. Finally, heterogeneity of clinical presentation and disease course is described in the context of multiple contributing factors, highlighting the complexity of AD. By integrating imaging, fluid biomarkers, genetics, and clinical measures, ADNI provides a comprehensive research dataset for unraveling mechanisms underlying AD progression.

We report the case of a previously healthy, 6-year-old boy who presented with 2 days of generalized body aches. Given a recent viral illness with cough and congestion, the emergency department’s initial diagnosis of the condition was viral myositis. He was admitted for pain treatment. During his hospitalization, he developed worsening pain, decreased mobility, and intermittent nocturnal desaturations. The team elicited additional history of snoring and witnessed apneas, which raised concern for obstructive sleep apnea. They consulted pulmonology who was concerned for central sleep apnea and respiratory depression and recommended consulting neurology. Neurology recommended a lumbar puncture, the results of which led to the eventual diagnosis. This case highlights the importance of critical reasoning and knowledge of the pediatric presentation of diseases that affect both adults and children.

Abstract Objective . Phase gating is a critical technique to mitigate tumor motion during radiotherapy, particularly in spot-scanned particle therapy where internal motion can interfere with dynamic spot scanning patterns and, simultaneously, introducing substantial range uncertainties. However, the current commercial state of the art in real-time phase prediction is challenged by patient-specific breathing variability as well as detection and delivery system latencies. This leads to suboptimal efficiency, mis-timed radiation delivery and requires frequent manual intervention. This study aims to improve phase prediction accuracy using deep learning (DL)-based time series forecasting to enable more accurate dose delivery. Approach . Retrospective breathing waveforms from 69 proton therapy patients, sampled at 30 Hz, were labeled with inspiratory peaks and assigned subjective regularity scores (four levels). DL models with various architectures were trained using waveform amplitude to predict current or future breathing phases. Model performance was evaluated using mean squared error, phase binning accuracy, and timing deviation for radiation on/off events. Bayesian optimization was used for hyperparameter tuning. Results were compared between models and against a commercial algorithm currently in clinical use. Main Results . The curated waveform dataset included 165 242 s for training, 24 057 s for validation, and 30 322 s for testing, with an additional 40 604 s from separate patients for extended validation. The long short-term memory and temporal fusion transformer models significantly outperformed the commercial algorithm, improving phase prediction accuracy by nearly 20% and reducing timing deviations across all regularity levels. Significance . DL-based time series forecasting may substantially improve breathing phase prediction accuracy over current clinically available methods, offering a more precise and reliable approach to phase-gated radiation delivery.

Abstract As an intrinsically mechanosensitive organ, the lung experiences a range of mechanical forces. Chronic obstructive pulmonary disease (COPD) involves abnormal macroscopic cellular and extracellular matrix (ECM) changes that impact mechanical properties of the lung. Mechanosensitive Piezo1/2 channels are expressed in the lung including on airway smooth muscle cells (ASM) that mediate cellular responses to stretch and ECM biomechanics. The expression and roles of Piezos in COPD lung ASM are not known. We hypothesized that Piezo expression and activation are altered in COPD lung ASM influencing ECM regulation. Distribution of Piezo proteins in ASM and epithelium of small airways of COPD stage II and IV vs. non-COPD controls was assessed using immunohistochemistry and ImageJ (n=10-17/group). Isolated ASM cells from control (n=6) vs. COPD stage II and IV patients (n=3 each stage) were exposed to stretch or the Piezo1 agonist Yoda1 followed by measurement of ECM gene and protein expression. Less Piezo2 staining was observed in COPD IV patients compared to controls, with lesser area and intensity of staining in the epithelial layer, and lower intensity of staining in ASM and small airways as a whole. Fura-2-based imaging of ASM Ca 2+ showed lower influx after Yoda1 exposure in COPD II compared to control and COPD IV. Gene expression of Piezo1 increased upon stretching in controls but not in COPD ASM, while Piezo2 protein expression decreased with stretching in all groups. Yoda1 treatment resulted in decreased collagen1 , fibulin1 and periostin gene and collagen 1 and periostin protein expression in ASM. Overall, these results support a role for Piezo activation in abnormal ECM-ASM cell crosstalk in COPD.

Abstract Spatial transcriptomics has been widely applied to study the spatial distribution of cell types, cell states, and specific gene expression in tissue samples. However, we show that there is a prevalent transcript leakage problem in spatial transcriptomics data, where transcripts expressed by a cell diffuse to its neighborhood and are recurrently detected in the nearby cells. By analyzing published data sets, we show that this problem is general across data produced from different tissues and different species using different imaging-based and sequencing-based spatial transcriptomics platforms. It affects both upstream tasks such as expression quantification as well as downstream tasks such as cell-type annotation and detection of spatially-dependent gene expression. To tackle the transcript leakage problem, we propose a reference-free Bayesian model-based method, DeLeakage, which cleans up the data much more effectively than existing denoising methods. DeLeakage also improves cell-type annotation and avoids false detection of spatially dependent expression.

Transitions from inpatient rehabilitation to home critically affect patient recovery and caregiver well-being. Social determinants of health (SDoH) shape these outcomes yet remain underexamined in rehabilitation settings. The objective of this study was to examine the prevalence of SDoH on patient and caregiver experiences during the first 30 days following discharge from a multi-site inpatient rehabilitation facility in the southeastern United States and explore patterns of patient satisfaction and caregiver burden that can influence care transitions. A prospective cross-sectional descriptive study surveyed 61 patients and 50 caregivers using validated instruments assessing SDoH, communication, discharge preparedness, and caregiver burden. Social isolation, affecting 18% of patients and 10% of caregivers, was the most prevalent challenge. Additional challenges include health literacy and transportation barriers. Caregivers experienced substantial burden: 60% decline in social activities, 50% decreased energy, and 40.9% negative physical health effects. However, 58.1% reported strengthened patient relationships. This study identifies the importance of care continuity and SDoHs after inpatient rehabilitation. Interdisciplinary interventions focused on these key challenges are essential for improving outcomes.

Diffuse large B-cell lymphoma (DLBCL), the most common type of lymphoma, arises from various pathogenic mechanisms including gene translocations and fusions. Detection of gene rearrangements using fluorescence in situ hybridization (FISH) is a standard practice for DLBCL diagnosis and guides treatment decisions. High-throughput chromosome conformation capture (Hi-C) DNA sequencing is a next-generation sequencing-based technology to identify genome-wide rearrangements using a single assay. In this study, Hi-C sequencing was performed using FFPE tissues from 159 patients with DLBCL, and identified 746 cancer genes at or proximal to the rearrangement breakpoints with a total of 1903 occurrences. Focusing on clinically important rearrangements, Hi-C detected 102 rearrangements of MYC, BCL2, and/or BCL6 in 92 patients and revealed the fusion partners, including 25 rearrangements missed by FISH. Causes of FISH negative results included FISH-cryptic breakpoints, complex or faint FISH signals, low percentage of FISH positivity, and issues related to tissue fixation. Moreover, in 20 patients (12.6%), Hi-C sequencing detected 22 rearrangements characteristic of other lymphoma types, including CCND1 rearrangements that could lead to reclassification as mantle cell lymphoma. Survival analysis for genome-wide rearrangements using machine learning models identified MYC, PD-L1, CCND1, BCL2, NTRK1/PRCC, RRAS, and FANCE rearrangements with significant prognostic effects in the DLBCL cohort. In conclusion, Hi-C sequencing detects gene rearrangements crucial for diagnosis in an unbiased and molecular manner and showed high sensitivity and specificity in our study. These advantages of Hi-C sequencing offer help to improve the workflow of clinical pathology laboratories, diagnostic precision, and treatment of large B-cell lymphoma.