Citations

Human diseases are complex and arise from the coordinated action of multiple genes and their protein products. Genes’ behaviors extend beyond genetic variants, mutations, and differential expressions. Their coordinated activity across biological scales (molecules, cells, tissues, organs) produces emergent behaviors that shape health and disease. These emergent behaviors span time and space and are often hard to measure directly from observation when using standard experimental measurements. Yet these “hidden” or latent gene characteristics can be powerful drivers of disease. We propose a Mini-Galaxy Model (MGM), a systems-level AI-driven network framework that models cells as “mini-galaxies” composed of multilayered biological information, with each layer encoding a different dimension of genes’ behavior. Here, we delineate a strategy on how to construct and compare MGMs across health and disease and map their etiological relatedness. We also operationalize the MGM as a discovery platform for translational medicine, offering modules to allow target prioritization and editing. By reframing human diseases as the result of emergent behavior of multilayered multimode biological networks and their perturbations, the MGM yields actionable rules to streamline biomarker discovery, guide target selection and enable rational design of combinatorial interventions, and accelerate drug repurposing.

Disclaimer: These guidelines are intended for educational use to build the knowledge of physicians and other health professionals in assessing the conditions and managing the treatment of patients undergoing extracorporeal life support (ECLS)/ECMO and describe what are believed to be useful and safe practice for ECLS and ECMO. The aim of clinical guidelines was to help clinicians to make informed decisions about their patients. However, adherence to a guideline does not guarantee a successful outcome. Healthcare professionals must make their own treatment decisions about care on a case-by-case basis, after consultation with their patients, using their clinical judgment, knowledge, and expertise. These guidelines do not take the place of physicians’ and other health professionals’ judgment in diagnosing and treatment of patients. These guidelines are not intended to and should not be interpreted as setting a standard of care or being deemed inclusive of all proper methods of care nor exclusive of other methods of care directed at obtaining the same results. The ultimate judgment must be made by the physician and other health professionals and the patient considering all the circumstances presented by the individual patient, and the known variability and biologic behavior of the clinical condition. These guidelines reflect the data at the time the guidelines were prepared; the results of subsequent studies or other information may cause revisions to the recommendations in these guidelines to be prudent to reflect new data, but ELSO is under no obligation to provide updates. In no event will ELSO be liable for any decision made or action taken in reliance upon the information provided through these guidelines.

ABSTRACT The epidemiology of myelodysplastic syndromes/neoplasms (MDS) is challenging to define due to inconsistent reporting, complex diagnostic procedures, and evolving diagnostic criteria. Using the National MDS Natural History Study—a prospective cohort with centrally adjudicated histopathology and genetic variant review—we characterized the landscape of MDS across the United States and identified differences across demographics. Among 2115 participants, 64% (1346) had an MDS spectrum condition, including MDS (24%), MDS/myeloproliferative neoplasm (5%) and precursor conditions—clonal cytopenia of undetermined significance (22%) and idiopathic cytopenia/dysplasia of undetermined significance (13%). The median age was 74 years, and participants were predominantly male (66%), White (91%), and Non‐Hispanic (92%). Myeloid‐associated variants were detected in 68% of participants, most commonly in TET2, DNMT3A, ASXL1, SF3B1, and SRSF2 . Black, compared to White, participants were younger at diagnosis (69 vs. 74 years, p = 0.01), had equal or increased prevalence of higher‐risk MDS, lower hemoglobin, and higher peripheral blood blasts, yet were less likely to receive MDS‐directed therapy (14% vs. 42%, p = 0.008). Black and Hispanic participants had fewer detectable gene mutations than White participants. Females had lower variant allele frequencies and fewer RNA splicing gene mutations than males. After multivariable adjustment, TP53 mutations, MDS diagnosis, and higher‐risk disease were associated with worse progression‐free and overall survival; age was also associated with overall survival. Black race trended toward improved progression‐free survival. These findings highlight the need for enhanced understanding of MDS pathogenesis across patient groups and refined prognostic tools to improve personalized management of MDS spectrum conditions. Trial Registration: ClinicalTrials.gov identifier: NCT02775383

Background Breast phyllodes tumours (PT) are rare biphasic neoplasms consisting of epithelial and stromal components. They are classified into benign, borderline and malignant categories. Diagnosing and grading PTs present a challenge for pathologists, as there are multiple histological parameters and their own tiers. We aim to investigate the potential role of artificial intelligence (AI) as a diagnostic aid in determining PT grade. Materials and methods We investigated 15 PT whole slide images (WSIs), comprising 5 benign, 5 borderline and 5 malignant cases. We sought to classify and retrieve the most relevant WSIs by matching histological features at different patch sizes, using the Yottixel framework for WSI processing. Patches were extracted at a 20× magnification level. We then used the KimiaNet to extract feature vectors and transformed these into barcode representations. Barcodes of a query WSI were compared with those of others in the archive, allowing us to identify the most similar WSI and determine the PT grades from histological similarities. Results We utilized ‘majority‐n accuracy’ as a measure of correctness, that is when the majority of the top‐n search results have the correct diagnosis as the query patient. We achieved a maximum reported accuracy of 67%, with a 3000 × 3000 patch size when grading PT at majority voting with n = 4. Conclusion Despite the small sample size and absence of fine‐tuning, our study demonstrated the potential of AI‐based PT grade stratification using various patch sizes through histological matching. This serves as a preliminary proof of concept, with the prospect of refinement for potential routine clinical application.

Discoidin Domain Receptor 2 (DDR2) is a collagen-activated tyrosine kinase required for bone and tooth development as well as regeneration of calvarial and long bones. Although DDR2 is expressed in alveolar bone, its functions in this site have not been previously examined. The present study used global and conditional knockout approaches and lineage tracing to examine the functions of DDR2 in alveolar bone formation during tooth socket healing. First molars were extracted from the maxillae of wild-type and globally Ddr2 -deficient ( Ddr2 LacZ/LacZ ) mice, and socket healing was measured after 1, 2, or 4 wk. At all times, Ddr2 inactivation significantly reduced socket healing. These changes were associated with decreased cell proliferation 3 d after extraction without any detectable changes in apoptosis. In addition, collagen fibril orientation, measured using Picrosirius Red staining under polarized light, was disrupted in tooth sockets from Ddr2 -deficient mice. For lineage tracing, 4-wk-old Ddr2 mer-cre-mer ; R26R tdTomato and Gli1 CreERT2 ; R26R tdTomato mice were induced with tamoxifen, first molars were extracted, and socket healing was examined after 1, 3, or 7 d. In both cases, tdTomato+ cells migrated into sockets, where they sequentially co-localized with preosteoblast and osteoblast markers. Thus, both DDR2 + and GLI1 + cells contribute to socket healing. The considerable overlap observed between DDR2 + and GLI1+ cells suggested that DDR2 functioned in GLI1 + cells, which are known to have skeletal progenitor properties. Consistent with localization data, conditional knockout ( Gli1 CreERT2 ; Ddr2 fl/fl ) mice exhibited reductions in socket healing 1 wk postextraction, although the inhibition of socket repair was less than that seen in global Ddr2 knockouts. In summary, this work demonstrates a role for DDR2 in alveolar bone repair, a finding that may have therapeutic implications for the treatment of alveolar bone loss associated with periodontal disease and other disorders.

ABSTRACT 162 patients with relapsed secondary central nervous system lymphoma (R‐SCNSL) (median age, 65 years; male, 59.9%) including central nervous system (CNS)‐only ( n = 120) and concomitant CNS/systemic relapse ( n = 42) were retrospectively analyzed. Overall, 21.9% of patients were classified as high risk according to the CNS International Prognostic Index (CNS‐IPI). Several biological and clinical features were significantly associated with leptomeningeal involvement, including double‐ or triple‐hit (DHL/THL) status, MYC rearrangement, negative BCL6 expression by IHC, bone marrow involvement, and concomitant R‐SCNSL. Multivariable analysis showed that leptomeningeal involvement independently predicted inferior OS and was associated with a 98% increase in the hazard of death compared with parenchymal relapse (HR = 1.98, 95% CI: 1.20–3.26, p = 0.008). Based on anatomical localization, R‐SCNSL was classified into four subtypes: parenchymal‐only involvement (parenchymal‐CNS [P‐CNS], 68/42%) and parenchymal involvement plus systemic relapse (parenchymal‐concomitant [P‐concomitant], 17/10.5%); and leptomeningeal with or without parenchymal involvement (leptomeningeal‐CNS [LM‐CNS], 52/32.1%) and leptomeningeal with systemic relapse (leptomeningeal‐concomitant [LM‐concomitant], 25/15.4%). This anatomical classification significantly impacted OS and PFS ( p < 0.001). Two‐year OS and PFS were 58.2% and 29.1% for P‐CNS, 32.4% and 17.7% for P‐concomitant, 22% and 13.9% for LM‐CNS, and 7.1% and 0% for LM‐concomitant, respectively. ASCT showed a trend toward improved survival among patients with a response (CR/PR) in a 4‐month landmark analysis. These findings support the clinical application of the anatomical classification in the management of R‐SCNSL.

Abstract Objectives Traditional laboratory regulatory frameworks provide robust guidance for conventional clinical testing but lack requirements for data documentation for artificial intelligence and machine learning (AI/ML) solutions. This gap creates significant risks since AI solutions directly inherit patterns, biases, and limitations from their training data. Here, we describe the development and implementation of a comprehensive data documentation checklist with accompanying data lineage for use within an AI lifecycle framework for clinical laboratories. Methods Building on the previously established Clinical AI Readiness Evaluator (CARE) framework, we developed a comprehensive data checklist and data lineage methodology through a multiphase process, including (1) comprehensive review of existing AI/ML data documentation frameworks, (2) focused meetings with 3 institutional AI operations teams, and (3) 3 rounds of iterative refinement by our multidisciplinary team. The checklist’s effectiveness was then assessed using 3 diverse AI/ML projects moving through the CARE framework. Results The CARE Data Checklist and Data Lineage provide a structured approach to documenting critical aspects of datasets used in AI/ML projects, including data composition, demographics, collection methods, labeling processes, usage constraints, maintenance requirements, and a data readiness assessment. The checklist addresses unique data-centric challenges of AI/ML applications, facilitating transparency, reproducibility, and regulatory compliance. Conclusions The CARE Data Checklist and Data Lineage serve as both a technical guide and a communication tool bridging gaps between technical and clinical stakeholders. By working on these documents early in the AI lifecycle, laboratories can anticipate and address data-related challenges, ultimately saving time, optimizing resources, and improving the reliability of AI-augmented laboratory solutions.

Summary Physical forces shape cell behavior, yet how they integrate with signaling to control fate and disease remains unclear. The alveolar epithelium is patterned by FGF signaling and mechanical stretch, but how these cues specify AT1 and AT2 cells is poorly understood. Here we show that cell membrane tension (CMT) is a conserved regulator of epithelial fate in mouse and human lungs. CMT drops before differentiation and is spatially patterned, defining where bipotent progenitors acquire AT1 or AT2 identity. Lower CMT enhances FGFR2 endocytosis and ERK signaling to drive AT2 differentiation and permits architectural remodeling that enables stretch-mediated YAP/TAZ nuclear entry for AT1 maturation. β-catenin elevates CMT cell-intrinsically independent of its role in canonical WNT transcription, while embedding, osmotic compression, or fibroblast wrapping elevate CMT extrinsically. Combined intrinsic and extrinsic tension traps alveolar epithelial cells in a KRT8⁺ transitional state seen in fibrotic lungs. Membrane tension thus integrates physical and molecular cues linking morphogenesis to fibrosis. Graphical Abstract In Brief We identify a conserved drop in cell membrane tension (CMT) that gates epithelial fate transitions across mouse and human lungs. In bipotent progenitors, reduced CMT promotes Alveolar Type 2 (AT2) fate via FGFR2 endocytosis and ERK signaling, as well as Alveolar Type 1 (AT1) fate by enabling architectural remodeling required for YAP/TAZ nuclear entry. We further show that intrinsic β-catenin and extrinsic confinement cues, including mesenchymal contact, converge to elevate CMT, restricting differentiation and—in adult AT2s—inducing a KRT8⁺ transitional state associated with fibrosis. Highlights Cell membrane tension drops before differentiation and is required for AT1 and AT2 fate acquisition. Reduced tension enhances FGFR2 endocytosis and ERK signaling to drive AT2 specification. Reduced tension permits architectural remodeling and YAP/TAZ nuclear entry required for AT1 maturation. Intrinsic β-catenin and extrinsic confinement elevate CMT to restrict differentiation and together strongly induce a KRT8⁺ transitional state associated with fibrosis.