Development

How embryonic cells generate large clones of cells in the adult represents a fundamental question in biology. Here, using melanocyte stem cells (McSCs) in the zebrafish as a model, we explore the function of the master melanocyte transcription factor (MITF) in safeguarding McSCs in embryonic development and their potential to pigment large clones in the adult. MITF is well known is for its role in the specification of melanoblasts from the neural crest (NC) and their differentiation into melanocytes, yet little is known about how this activity shapes the stem cell lineages. Here, we use live imaging coupled with single-cell transcriptomics and lineage tracing to show that MITF (mitfa in zebrafish) protects the melanocyte stem cell (McSC) fate in zebrafish. Utilizing a temperature sensitive mitfavc7 mutant, we show loss of Mitfa leads to a surprising premature and aberrant expansion of McSC progeny at the niche during embryogenesis, coupled with novel emergent transcriptional cell states. Linage tracing of McSCs from the embryonic to juvenile stages reveals Mitfa activity is subsequently required in regeneration by Schwann cell-like and melanocyte stem cell progenitors that serve as a reservoir for fast-responding pigment progenitors. Thus, the impact of Mitfa loss on the melanocyte lineage is cell-state and stage-specific. The emergent cell states upon mitfa loss may have important implications for our understanding the loss of MITF activity in human genetic disease and melanoma.

Fluorescent in situ hybridization (FISH) enables highly sensitive, high-resolution detection of gene transcripts. Moreover, by employing multiple probes, this technique allows for multiplexed, simultaneous detection of distinct gene expression patterns spatiotemporally, making it a valuable spatial transcriptomics approach. Owing to these advantages, FISH techniques are rapidly being adopted across diverse areas of basic biology. However, conventional protocols often rely on volatile, toxic reagents such as formalin or methanol, posing potential health risks to researchers. Here, we present a safer protocol that replaces these chemicals with low-toxicity alternatives, without compromising the high detection sensitivity of FISH. We validated this protocol using both in situ hybridization chain reaction (HCR) and signal amplification by exchange reaction (SABER)-FISH in frozen sections of various model organisms, including mouse (Mus musculus), amphibians (Xenopus laevis and Pleurodeles waltl), and medaka (Oryzias latipes). Our results demonstrate successful multiplexed detection of morphogenetic and cell-type marker genes in these model animals using this safer protocol. The protocol has the additional advantage of requiring no proteolytic enzyme treatment, thus preserving tissue integrity. Furthermore, we show that this protocol is fully compatible with EGFP immunostaining, allowing for the simultaneous detection of mRNAs and reporter proteins in transgenic animals. This protocol retains the benefits of highly sensitive, multiplexed, and multimodal detection afforded by integrating in situ HCR and SABER-FISH with immunohistochemistry, while providing a safer option for researchers, thereby offering a valuable tool for basic biology.

Understanding how cells migrate through confined environments is crucial for elucidating fundamental biological processes, including cancer invasion, immune surveillance, and tissue morphogenesis. The nucleus, as the largest and stiffest cellular organelle, often limits cellular deformability, making it a key factor in migration through narrow pores or highly constrained spaces. In this work, we introduce a geometric surface partial differential equation (GS-PDE) model in which the cell plasma membrane and nuclear envelope are described as evolving energetic closed surfaces governed by force-balance equations. We replicate the results of a biophysical experiment, where a microfluidic device is used to impose compressive stresses on cells by driving them through narrow microchannels under a controlled pressure gradient. The model is validated by reproducing cell entry into the microchannels. A parametric sensitivity analysis highlights the dominant influence of specific parameters, whose accurate estimation is essential for faithfully capturing the experimental setup. We found that surface tension and confinement geometry emerge as key determinants of translocation efficiency. Although tailored to this specific setup for validation purposes, the framework is sufficiently general to be applied to a broad range of cell mechanics scenarios, providing a robust and flexible tool for investigating the interplay between cell mechanics and confinement. It also offers a solid foundation for future extensions integrating more complex biochemical processes such as active confined migration.

BackgroundPathogenic desmin (DES) variants have been implicated in early-onset atrial disease, yet the mechanisms by which desmin dysfunction alters atrial structure and function remain unclear. Desmin anchors the cytoskeleton to the nuclear envelope (NE) through the linker of nucleoskeleton and cytoskeleton (LINC) complex, suggesting that defects in this network may drive atrial cardiomyopathy. MethodsHuman desmin wild-type (WT) and the pathogenic variants p.S13F, p.N342D, and p.R454W were stably expressed in HL-1 atrial cardiomyocytes. Desmin organization, nuclear morphology, LINC-complex integrity (nesprin-3, lamin A/C), and DNA leakage, assessed by cyclic GMP-AMP synthase (cGAS), were analyzed by confocal microscopy. Action potential duration (APD) and calcium transients (CaT) were measured optically. Human myocardium samples from DES variant carriers were analyzed for validation. Data-independent acquisition (DIA) mass spectrometry profiled atrial proteomes from desmin-network (DN) and titin variant carriers and controls. The heat-shock proteins (HSPs) inducer geranylgeranylacetone (GGA) was evaluated for rescue effects. Resultsp.N342D caused severe filament-assembly defects with prominent perinuclear aggregates, whereas p.S13F showed mixed phenotypes with frequent perinuclear aggregates, and p.R454W largely preserved filamentous networks. p.N342D and p.S13F induced nuclear deformation with disrupted nesprin-3 and lamin A/C distribution. In p.N342D and p.S13F, desmin aggregates drove focal lamin A/C accumulation, nuclear envelope (NE) rupture, DNA leakage, and increased cGAS activation. DES variants significantly shortened APD20/90 and reduced CaT amplitude, indicating pro-arrhythmic electrical remodeling. Atrial proteomics revealed a DN-specific signature enriched for cytoskeletal, NE, intermediate filament, and chaperone pathways, consistent with the structural injury observed in vitro. GGA prevented desmin aggregation and nuclear morphology changes, and mitigated APD shortening in p.N342D-expressing cardiomyocytes. Human myocardium from DES variant carriers showed concordant desmin aggregation and polarized lamin A/C distribution. ConclusionsDES variants induce a desmin-dependent atrial cardiomyopathy characterized by cytoskeletal disorganization, disruption of LINC-complex, NE rupture with DNA leakage, and pro-arrhythmic electrophysiological remodeling. These findings provide mechanistic insight into how DN variants promote atrial disease. HSPs induction by GGA partially restores structural and functional integrity, identifying a potential therapeutic approach for desmin-related atrial cardiomyopathy. Clinical perspectiveWhat is new? O_LIPathogenic DES variants induce a previously unrecognized atrial cardiomyopathy characterized by desmin aggregation, and desmin-network (DN) collapse, disruption of the linker of nucleoskeleton and cytoskeleton (LINC) complex, and nuclear envelope rupture with DNA leakage. C_LIO_LIVariants that lead to desmin aggregation (e.g., p.N342D) cause focal lamin A/C polarization, cyclic GMP-AMP synthase (cGAS) activation, and structural injury at the nuclear envelope. C_LIO_LIDES variants produce pro-arrhythmic electrical remodeling, including action potential duration shortening and impaired Ca{superscript 2} handling in HL-1 atrial cardiomyocytes. C_LIO_LIAtrial proteomics from DN variant carriers reveals enrichment of pathways related to cytoskeletal, nuclear envelope, intermediate filament, and chaperone, supporting a desmin-dependent remodeling program. C_LIO_LIThe heat-shock protein inducer geranylgeranylacetone (GGA) prevents desmin aggregation, restores nuclear morphology, and mitigates electrical and Ca{superscript 2} handling remodeling. C_LI What are the clinical implications? O_LIThese findings establish DN dysfunction as a distinct cause of atrial cardiomyopathy, providing a mechanistic basis for the association between pathogenic DES variants and atrial arrhythmias, including atrial fibrillation. C_LIO_LINuclear envelope rupture and cytosolic DNA leakage represent new mechanistic evidence which links cytoskeletal injury and atrial arrhythmogenesis. C_LIO_LIIdentifying structural vulnerability in DES variant carriers fosters awareness of genetic counseling for atrial disease, enabling early detection and risk stratification. C_LIO_LIThe protective effects of GGA suggest that restoring proteostasis may be a therapeutic strategy for desmin-related atrial cardiomyopathy and potentially other genetic atrial diseases. C_LI Novelty and significance statementO_ST_ABSNoveltyC_ST_ABSThis study identifies a desmin-dependent atrial cardiomyopathy driven by cytoskeletal aggregation, LINC-complex disruption, and nuclear envelope rupture with DNA leakage. We show that pathogenic DES variants are associated with pro-arrhythmic molecular remodeling and that human atrial proteomics confirm nuclear envelope and cytoskeletal injury as core features. Importantly, the heat-shock protein-inducer GGA rescues structural, molecular, and electrophysiological defects, revealing a modifiable pathway in desmin-mediated atrial disease. SignificanceThese findings provide the first integrated mechanistic explanation linking DN variants to atrial cardiomyopathy. By uncovering nuclear envelope rupture and cGAS activation as key drivers of atrial cardiomyopathy, this work expands the molecular framework for inherited atrial disease and highlights proteostasis enhancement as a potential therapeutic strategy for patients carrying DES and related cytoskeletal variants. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=166 HEIGHT=200 SRC="FIGDIR/small/26348559v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@1fb0bfborg.highwire.dtl.DTLVardef@cfc00borg.highwire.dtl.DTLVardef@1493578org.highwire.dtl.DTLVardef@1556b61_HPS_FORMAT_FIGEXP M_FIG C_FIG

Drug-tolerant persisters (DTPs) represent a major obstacle to durable responses in targeted cancer therapy. DTPs are commonly described as distinct single-cell states that survive drug treatment via reversible, non-genetic mechanisms and drive tumor recurrence. Recent work demonstrates that multiple DTPs can coexist, reflecting diversity in lineage, signaling programs, or stress responses. However, each DTP is still generally viewed as a uniform cellular phenotype. Building on our prior work describing a population-level DTP termed "idling" [Paudel et al., Biophys. J. (2018) 114, 1499-1511], here we present evidence supporting a fundamentally different view: that DTPs are not single-cell states, but rather heterogeneous populations composed of multiple sub-states with distinct division and death rates that balance to produce near-zero net population growth. Using single-cell transcriptomics and lineage barcoding, we identify multiple phenotypic states within idling DTP populations, with reduced heterogeneity compared to untreated populations, and find that idling DTP cells emerge from nearly all lineages. Transcriptomic and functional analyses further reveal altered ion-channel activity in idling DTPs, which we confirm experimentally. Moreover, drug-response assays reveal increased susceptibility of idling DTPs to ferroptosis, a non-apoptotic form of regulated cell death, indicating the emergence of vulnerabilities associated with drug tolerance. Altogether, our results support a population-level view of tumor drug tolerance in which DTPs comprise stable collections of phenotypic states, shaped by treatment-defined phenotypic landscapes, which are potentially vulnerable to subsequent interventions. This perspective implies that eradicating DTPs will require a fundamental shift away from cell-type-centric strategies toward sequential treatments that progressively reduce phenotypic heterogeneity by modulating the molecular and cellular processes that establish the DTP landscape, an approach previously termed "targeted landscaping."

Neuronal migration is a vital process that positions billions of neurons to create a functional brain. To navigate the constrained microenvironments within the cortex, precise control over the nuclear mechanics in migrating neurons is indispensable. Here, we show that Lamin B1 (LB1) regulates neuronal migration by modulating nuclear deformability. Excess LB1 in neurons halted migration without altering laminar identity or overall gene expressions in vivo, while in vitro, it elevated nuclear stiffness and impaired neuronal motility in confined spaces. Moreover, mispositioned neurons resulted in electrophysiological defects in the brain. Computational modeling predicted a temporal relationship between nuclear deformation and enhanced migration velocity, which was validated experimentally through live imaging. Notably, cerebral organoid assays using iPS cells established from patients with LMNB1 duplication exhibited impaired neuronal migration in a human model. Collectively, these findings demonstrate that LB1 is a critical regulator of nuclear mechanics, ensuring the accurate spatiotemporal positioning of neurons.

Intermuscular adipose tissue (IMAT) expansion is closely associated with cardiometabolic disease, yet its cellular organization and regulatory mechanisms remain poorly defined. Here, we define a human IMAT gene signature using bulk transcriptomics and identify candidate regulators for IMAT function including adipogenic transcription factor early B-cell factor 2 (EBF2). To determine how these programs are organized in situ, we mapped this signature in a mouse model of diet-induced CMD using spatial transcriptomics. We found that IMAT expansion occurs within discrete stromal niches surrounding muscle fibers, characterized by coordinated activation of adipogenic, extracellular matrix, inflammatory, and metabolic pathways. Spatial analyses showed that fibro-adipogenic progenitor (FAP) abundance does not predict adipocyte formation, supporting a model of localized and context-dependent lineage transitions. Cross-species comparison revealed partial conservation of human IMAT gene programs, validating the mouse model and highlighting species-specific features. Functional experiments in human primary myoblasts showed that EBF2 is sufficient to induce adipogenic reprogramming. Our findings establish IMAT as an active, spatially organized remodeling niche and identify lineage plasticity as a central mechanism driving its expansion in metabolic disease

Gene networks (GNs) encode diverse molecular relationships and are central to interpreting cellular function and disease. The heterogeneity of interaction types has led to computational methods specialized for particular network contexts. Large language models (LLMs) offer a unified, language-based formulation of GN inference by leveraging biological knowledge from large-scale text corpora, yet their effectiveness remains sensitive to prompt design. Here, we introduce Gene-Relation Adaptive Soft Prompt (GRASP), a parameter-efficient and trainable framework that conditions inference on each gene pair through only three virtual tokens. Using factorized gene-specific and relation-aware components, GRASP learns to map each pair's biological context into compact soft prompts that combine pair-specific signals with shared interaction patterns. Across diverse GN inference tasks, GRASP consistently outperforms alternative prompting strategies. It also shows a stronger ability to recover unannotated interactions from synthetic negative sets, suggesting its capacity to identify biologically meaningful relationships beyond existing databases. Together, these results establish GRASP as a scalable and generalizable prompting framework for LLM-based GN inference.

Lightweight epidemic calculators are widely used for teaching and rapid scenario exploration, yet many omit the methodological detail needed for scientific reuse. We present a browser-native SIR calculator that exposes forward Euler and classical fourth-order Runge--Kutta (RK4) integration alongside epidemiologically interpretable outputs and a population-conservation diagnostic. The implementation is anchored to analytical properties of the deterministic SIR system, including the epidemic threshold, the peak condition, and the final-size relation. Benchmark experiments show that RK4 is essentially step-size invariant over practical discretizations, whereas Euler at a coarse one-day step overestimates peak prevalence by 3.97% and final size by 0.66% relative to a fine-step RK4 reference. These results demonstrate that browser-based tools can support publication-quality computational narratives when solver choice, diagnostics, and assumptions are treated as first-class outputs.

Orphan genes, lacking homologs in other species, are systematically found across genomes. Their presence may result from extensive divergence from pre-existing genes or from de novo gene birth, which occurs when a gene emerges from a previously non-genic region. In this study, we identified orphan genes in the genomes of globally distributed plant-parasitic nematodes of the genus Meloidogyne and investigated their origins, evolution, and characteristics. Using a comparative genomics framework across 85 nematode species, we found that 18% of Meloidogyne genes are genus-specific, transcriptionally supported orphans. By combining ancestral sequence reconstruction and synteny-based approaches, we inferred that 20% of these orphan genes originated through high divergence, while 18% likely emerged de novo. Proteomic and translatomic evidence confirmed the translation of a subset of these genes, and feature analyses revealed distinctive molecular signatures, including shorter length, signal peptide enrichment, and a tendency for extracellular localization. These findings highlight orphan genes as a substantial and previously underexplored component of the Meloidogyne genome, with potential roles in their worldwide parasitism.

Patients who participate in intracranial neuroscience research make invaluable contributions to our understanding of the brain, accelerating the development of neurotechnological interventions. Engagement of patients as part of this research presents unique challenges, where study goals can be distant from immediate clinical applications and require specialized domain knowledge. Yet methods for meaningfully integrating patient communities as part of these research efforts is essential, as intracranial neuroscience guides the application of artificial intelligence for understanding and enhancing human cognition. In order to identify what patients consider meaningful research engagement we interviewed individuals who participated in a study during their Deep Brain Stimulation (DBS) surgery and attended a group event where they interacted with our research team. Analysis of semi-structured interviews identified four main themes: interest in science and the future of clinical care, contributing to science to improve lives, connecting with others, and accessibility considerations. Based on these insights, we propose strategies for transformational participation of patient communities in intracranial neuroscience research with respect to engagement objectives, communication and scope. This approach offers a foundation for sustaining relationships between scientists and communities rooted in trust and transparency, to ensure that impacts of neurotechnology on human health and cognition are aligned with patient needs as well as desired public values.

End-stage liver disease (ESLD) is one of the leading causes of death worldwide. Currently, the only curative option for patients with ESLD is liver transplantation. However, the demand for donor livers far exceeds the available supply, partly because many potentially viable livers are discarded following biopsy evaluation. While biopsy is the gold standard for assessing liver histological features related to graft quality and transplant suitability, it often leads to high discard rates due to its susceptibility to sampling errors and limited spatial coverage. Besides, biopsy is invasive, time-consuming, and unavailable in clinical facilities with limited resources. Here, we present an AI-assisted photoacoustic/ultrasound (PA/US) imaging framework for quantitative assessment of human donor liver graft quality and transplant suitablity at the whole-organ scale. With multimodal volumetric PA/US images as the input, our deep-learning (DL) model accurately predicted the risk level of fibrosis and steatosis, which indicate the graft quality and transplant suitability, when comparing with true pathological scores. DL also identified the imaging modes (PAI wavelength and B-mode USI) that correlated the most with prediction accuracy, without relying on ill-posed spectral unmixing. Our method was evaluated in six discarded human donor livers comprising sixty spatially matched regions of interest. Our study will pave the way for a new standard of care in organ graft quality and transplant suitability that is fast, noninvasive, and spatially thorough to prevent unnecessary organ discards in liver transplantation.

Semaglutide has shown benefit in metabolic dysfunction-associated steatohepatitis (MASH), but real-world evidence across longitudinal liver phenotypes remains limited, particularly regarding how liver remodeling relates to weight loss and dose exposure. Using a de-identified federated electronic health record network spanning more than 29 million patients in the United States, including 489,785 semaglutide-treated adults, we analyzed 6,734 patients with baseline liver disease burden. We find that higher attained pre-landmark (0-2 years) semaglutide dose was associated with lower post-landmark (2-4 years) risk of steatohepatitis, alcoholic liver disease, and all-cause mortality, whereas greater pre-landmark weight loss was associated with lower post-landmark risk of steatohepatitis, steatotic liver disease, and hepatorenal syndrome, indicating distinct dose- and weight-linked patterns of long-term liver benefits. These associations were notable because semaglutide prescribing was generally lower during the post-landmark period, raising the possibility of durable benefit beyond peak exposure. Towards better understanding mechanistic bases for liver protection, we performed a complementary longitudinal study of 326 adults with paired noninvasive liver elastography measurements before and after treatment initiation. Median liver stiffness decreased from 4.85 [3.02 - 7.20] to 3.9 [2.6 - 5.8] kPa after semaglutide initiation (median change = -0.38 kPa; p<0.001), with 194 of 326 patients (59.5%) showing lower follow-up stiffness. A clinically meaningful reduction of at least 20% was observed in 133 of 326 patients (40.8%), and 69 of 326 (21.2%) shifted to a lower fibrosis stage by prespecified elastography thresholds. Larger improvements were also seen in patients with higher baseline stiffness (p<0.001); notably 80% of patients with cirrhosis-range baseline stiffness ([&ge;]12.5 kPa) achieved [&ge;]20% improvement versus 29.5% with minimal baseline disease (p <0.001). The proportion achieving at least 20% stiffness improvement was similar across weight-loss strata, including patients with no weight loss or weight gain and those with at least 10% weight loss (38.0% in each group), and liver stiffness change showed negligible correlation with changes in weight, BMI, HBA1c, alanine aminotransferase, or aspartate aminotransferase. To provide biological context, single cell RNA analyses demonstrated sparse overall hepatic GLP1R expression (0.0239%), with enrichment in non-parenchymal niches including cholangiocytes, intrahepatic cholangiocytes, liver sinusoidal endothelial cells, and hepatic stellate cells implicated in fibrogenesis and vascular remodeling. Together, this real-world evidence suggests diverse liver benefits for semaglutide beyond weight-loss with intricate dose response relationships.

Automating Hierarchical Condition Category (HCC) assignment directly from unstructured electronic health record (EHR) notes remains an important but understudied problem in clinical informatics. We present HCC-Coder, an end to end NLP system that maps narrative documentation to 115 Centers for Medicare & Medicaid Services(CMS) HCC codes in a multi-label setting. On the test dataset, HCC-Coder achieves a macro-F1 of 0.779 and a micro-F1 of 0.756, with a macro-sensitivity of 0.819 and macro-specificity of 0.998. By contrast, Generative Pre-trained Transformer (GPT)-4o achieves highest score of a macro-F1 of 0.735 and a micro-F1 of 0.708 under five-shot prompting. The fine-tuned model demonstrates consistent absolute improvements of 4%-5% in F1-scores over GPT-4o. To address severe label imbalance, we incorporate inverse-frequency weighting and per-label threshold calibration. These findings suggest that domain-adapted transformers provide more balanced and reliable performance than prompt-based large language models for hierarchical clinical coding and risk adjustment.

Patterns of locus coeruleus (LC) activity and norepinephrine (NE) release during non-rapid-eye-movement (NREM) sleep suggest a critical role for the LC-NE system in offline modulation of forebrain circuits. NE transmission promotes synaptic plasticity and is required for memory consolidation, but the field has only begun to uncover how LC activity contributes to coordinated forebrain network dynamics. Hippocampal ripples, a hallmark of memory replay, are temporally coupled with thalamocortical oscillations; however, the circuit mechanisms underlying systems-level consolidation across larger brain networks remain incompletely understood. Here, using multi-site electrophysiology, we examined LC firing in relation to hippocampal ripples in freely behaving rats. LC activity and ripple occurrence were state-dependent and inversely related: heightened arousal was associated with increased LC firing and reduced ripple rates. At finer timescales, LC spiking decreased {approx}1-2 seconds before ripple onset, with the strongest modulation during awake ripples but minimal change during ripple- spindle coupling. These findings reveal state-dependent dynamics of LC-hippocampal interactions, positioning the LC as a key component of a cortical-subcortical network supporting systems-level memory consolidation.

Introduction The link between Human Papillomavirus (HPV) and cancer is well-established. In Singapore, bivalent HPV vaccines are subsidised for females, but not males. Economic analysis of HPV vaccination has generally assessed the costs to the health system, but this may not be as relevant to individual decision-making as potential lost income. We estimated the impact of bivalent HPV 16/18 vaccination on sick leave, unemployment, and premature mortality as a function of age and sex to understand the broader impact of HPV-related cancers. Methods We developed a population-level economic model to estimate lifetime income losses by diagnosis age, sex and cancer type. We applied sex- and cancer-specific Cox regressions to the Singapore Cancer Registry for annual predicted survival from 1992 to 2022. These were combined with census and employment data to estimate HPV-associated income losses in Singapore. Attributable fractions and vaccine effectiveness data for HPV 16/18 from the literature were used to estimate the effectiveness of bivalent HPV vaccination. Structural sensitivity analysis examined the role of 80% population coverage conferring herd immunity. Results The registry contained 17,294 individuals with an HPV-associated cancer diagnosis. Lost income was greatest for cervical cancer due to its high prevalence, however the losses per diagnosis were highest for oropharyngeal cancer. Bivalent HPV vaccination led to income benefits of $SGD1,397 [$895 to $1,838] in girls and -$62 [-$76 to -$48] in boys. A gender-neutral HPV vaccination of 80% of 15-year-old Singaporeans, conferring herd immunity, would have lifetime income protective benefits of $24.4m [$14.2m, $33.7m] per cohort, a five-fold return on investment. Conclusions In addition to avoiding healthcare costs and lost quality of life, parents should consider vaccination as a means of avoiding potential income losses. A national policy of gender-neutral HPV vaccination could deliver substantial income protection due to both individual vaccine protection and herd immunity.

BackgroundSubstance use initiation in adolescence is influenced by both genetic and environmental factors; however, large-scale genetic studies often treat initiation as a binary outcome and underuse longitudinal timing information. MethodsWe conducted time-to-event (survival) genome-wide association analyses (GWAS) of initiation for four outcomes--alcohol, nicotine, cannabis, and any substance use--using longitudinal follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study. We performed ancestry-stratified GWAS within European (EUR), African (AFR), and Hispanic (HISP) groups, applying consistent quality control and covariate adjustment. Summary statistics were harmonized across ancestries and meta-analyzed using inverse-variance weighted fixed-effects and DerSimonian-Laird random-effects models. We evaluated genomic inflation and heterogeneity (Cochrans Q and I2), identified independent lead variants at genome-wide and suggestive significance thresholds, and assessed cross-trait overlap of associated loci. ResultsIn the multi-ancestry meta-analysis, we observed suggestive association signals across traits (minimum p-values: alcohol [~] 1 x 10-7, any [~] 1 x 10-7, cannabis [~] 5 x 10-8, nicotine [~] 1 x 10-8). Nicotine initiation showed one genome-wide significant variant in both fixed- and random-effects meta-analyses (p < 5 x 10-8). Across traits, suggestive loci demonstrated limited overlap, with the strongest concordance between alcohol and any substance use, consistent with shared liability. Heterogeneity statistics indicated that some loci exhibited cross-ancestry variation in effect estimates. ConclusionsSurvival GWAS leveraging initiation timing can identify genetic signals that may be missed by binary designs and enables principled multi-ancestry synthesis. Our results highlight both shared and trait-specific genetic contributions to early substance initiation and provide a foundation for downstream functional annotation and integrative modeling with environmental risk factors. These findings demonstrate the value of incorporating developmental timing into genetic discovery and provide a framework for integrating longitudinal risk modeling with genomic analyses.

Background: Sezary syndrome (SS) is an aggressive leukemic variant of cutaneous T-cell lymphoma (CTCL) with distinct clinical and biological features compared to rarer entities such as primary cutaneous CD8+ aggressive epidermotropic cytotoxic T-cell lymphoma (PCAECTCL). Although recurrent genomic alterations in CTCL have been described, comparative analyses at the pathway level across biologically divergent subtypes remain limited. Here, we leveraged a conversational artificial intelligence (AI) platform for precision oncology to enable rapid, integrative, and hypothesis-driven interrogation of publicly available genomic datasets. Methods: We conducted a secondary analysis of somatic mutation and clinical data from the Columbia University CTCL cohort accessed via cBioPortal. Cases were stratified into SS (n=26) and PCAECTCL (n=13). High-confidence coding variants were curated and mapped to biologically relevant signaling pathways and functional gene categories implicated in CTCL pathogenesis. Pathway-level mutation frequencies were compared using Chi-square or Fisher's exact tests, with effect sizes quantified as odds ratios. Tumor mutational burden (TMB) was compared using the Wilcoxon rank-sum test. Subtype-specific co-mutation patterns were evaluated using pairwise association analyses and visualized through oncoplots and network heatmaps. Conversational AI agents, AI-HOPE, were used to iteratively refine cohort definitions, prioritize pathway-level signals, and contextualize findings. Results: TMB was comparable between SS and PCAECTCL (p = 0.96), indicating no significant difference in global mutational load. In contrast, pathway-centric analyses revealed marked qualitative differences. SS demonstrated enrichment of alterations in epigenetic regulators, tumor suppressor and cell-cycle control pathways, NFAT signaling, and DNA damage response mechanisms, consistent with transcriptional dysregulation and immune modulation. PCAECTCL exhibited relatively higher frequencies of alterations involving epigenetic regulators and MAPK pathway signaling, suggesting distinct oncogenic dependencies. Co-mutation analysis revealed a more constrained and focused interaction landscape in SS, whereas PCAECTCL displayed broader and more heterogeneous co-mutation networks, indicative of divergent evolutionary trajectories. Notably, ERBB2 mutations were significantly enriched between subtypes (p = 0.031), highlighting a potential subtype-specific therapeutic vulnerability. Conclusions: This study demonstrates that SS is distinguished from PCAECTCL not by increased mutational burden but by distinct pathway-level architectures, particularly involving epigenetic regulation, immune signaling, and transcriptional control. These findings generate biologically grounded, testable hypotheses for subtype-specific therapeutic targeting and underscore the value of conversational AI as a scalable framework for accelerating discovery in translational cancer genomics.

Effective predictive biomarkers for immune checkpoint inhibitor (ICI) therapy remain an unmet need across solid tumors. Here, we present an integrated spatial proteomics workflow that combines in situ proximity ligation assay with multiplexed immunofluorescence to directly resolve PD1/PDL1 signaling events at the level of defined cellular phenotypes and their spatial organization within intact tumor tissue. Applied as a proof of concept to tumor samples from patients with metastatic urothelial carcinoma treated with pembrolizumab, this approach reveals that PD1/PDL1 interactions specifically involving cytotoxic CD8CD3 T cells are significantly enriched in complete responders, while such interactions are rare in patients with progressive disease. This interaction defined T cell subset achieves superior discrimination of clinical response compared to single marker PDL1 expression or immune cell abundance alone. By integrating direct detection of protein protein interactions with high dimensional single cell phenotyping, our workflow provides a mechanistically informed, spatially resolved biomarker of functional immune engagement. Beyond urothelial carcinoma, this platform establishes a generalizable framework for translating spatial signaling biology into predictive tools for immunotherapy response across tumor types.

Background: Placental function is associated with congenital heart defects (CHD), frequently presenting with malperfusion lesions and small-for-gestational-age size. However, placental villous vasculature in the setting of CHD is understudied. This study evaluated differences in placental, neonatal, and maternal outcomes among maternal/infant dyads with versus without CHD. Methods: We conducted a gestational age- and fetal sex-matched retrospective case control study using specimens prospectively collected by a local biobank. Neonatal outcomes included birthweight, placental weight, and their ratio (placental efficiency). We estimated the proportion of placental villous tissue comprised of fetal vascular endothelial cells (%FVE) using anti-CD34 immunohistochemistry and a pixel count algorithm. Placental weight multiplied by %FVE estimated the grams of placental tissue comprised of villous vasculature (placental vascular index). Maternal outcomes included hypertensive disorders of pregnancy and gestational diabetes. We compared cases and controls using linear and logistic regression adjusted for maternal smoking and cold ischemia time. Stratified analyses examined associations by preterm birth status. Results: Dyads (n=34 with CHD, n=34 without CHD) had maternal age of 29.4 +/- 4.9 years and were 35.6 +/- 4.0 gestational weeks at delivery. Groups had similar placental, neonatal, and maternal parameters. Among preterm neonates, we observed small-to-moderate effect sizes indicating lower placental weight, %FVE, and placental vascular index, and higher placental efficiency, in CHD cases. Among term neonates, moderate effect sizes suggested lower birthweight, placental weight, and placental vascular index in CHD cases. Conclusions: Though differences between groups were not significant, moderate effect sizes suggested that placental vascularization was lower among preterm neonates with CHD.