Anti-CD19 chimeric antigen receptor (CAR) T-cell therapy can induce durable remissions in patients with large B-cell lymphoma (LBCL), yet outcomes remain variable. Reliable pre-treatment predictors of durable response remain limited, leaving a critical gap in patient management. To address this, we profiled pre-treatment plasma cell-free RNA (cfRNA) from 91 LBCL patients treated with axicabtagene ciloleucel (axi-cel, Yescarta) across three independent cohorts. We first demonstrated that signatures of "lymph node-like" tumor microenvironments (TMEs), previously identified in tumor biopsies and shown to correlate with favorable outcomes, are specifically elevated in the pre-treatment plasma cfRNA of responders, but not in matched peripheral blood mononuclear cells (PBMCs). These observations indicate that cfRNA captures TME tissue-derived signals not reflected in circulating immune cells. Next, using unbiased approaches, we identified additional cfRNA signatures associated with one-year clinical outcomes that capture the underlying biological landscape of treatment response. Collectively, these findings support pre-treatment plasma cfRNA as a minimally invasive surrogate of TME state to prospectively inform durable CAR T-cell therapy outcomes and guide risk stratification and TME-modulating adjunct therapies.

Intermicrobial and host-microbial interactions are critical for the functioning of the gut microbiome, but few tools are available to measure these interactions in situ. Here we report a method for broad spatial sampling of microbiome-host interactions in the gut at high resolution (1 µm). This method combines enzymatic in situ polyadenylation of both bacterial and host RNA with spatial RNA sequencing to increase bacterial RNA recovery and enable transcriptomic analysis of low-abundance and spatially restricted microbial taxa. We benchmark the method against existing spatial transcriptomic workflows, demonstrating improved sensitivity and resolution. Application of this method in a mouse model of intestinal neoplasia revealed the biogeography of the mouse gut microbiome as function of location in the intestine, frequent strong intermicrobial interactions at short length scales and tumour-associated changes in the architecture of the host-microbiome interface. This method is compatible with widely available commercial platforms for spatial RNA sequencing and can therefore be readily adopted to study the role of short-range, bidirectional host-microbe interactions in microbiome health and disease.

Canine acanthomatous ameloblastoma (CAA) is a locally invasive benign oral neoplasm that is difficult to distinguish from canine oral squamous cell carcinoma (COSCC) due to overlapping features. Previous studies using bulk RNA sequencing (RNA-seq) have demonstrated pronounced differences in programs related to hypoxia and cell proliferation. However, these studies lacked the resolution to elucidate the cellular heterogeneity of CAA relative to COSCC. We performed single-nucleus RNA-seq to define the cellular gene expression landscape of CAA, COSCC, and healthy gingiva. Across ∼205,000 nuclei, we identified two epithelial states uniquely enriched in CAA. The CAA-specific keratinocytes exhibited a neuronal-like expression program defined by synaptic regulators, KRAS-associated signaling pathways, and markedly elevated expression of PEG3 and ERBB4. These findings were validated by immunohistochemistry, which showed strong nuclear localization of PEG3 exclusively in CAA epithelium. A kinase inhibitor screen independently identified ERBB4 as a candidate therapeutic vulnerability, and pharmacologic inhibition with neratinib was effective. Together, these findings reveal a previously unrecognized neuroepithelial cell state that defines CAA, distinguishes it from COSCC, and reveals unique diagnostic and therapeutic signaling dependencies. Given the molecular/histopathologic parallels between CAA and human ameloblastoma, these data further position CAA as a naturally occurring comparative model for studying ameloblastoma therapeutic vulnerabilities.

Abstract Lymphatic dysfunction drives severe and often intractable human diseases, yet the cellular mechanisms that establish functional lymphatic vasculature remain poorly understood. In the intestine, lacteals are specialized lymphatic vessels that absorb dietary lipids and rely on surrounding villus smooth muscle to propel lymph, forming the muscular-lacteal complex (MLC). How distinct mesenchymal populations coordinate assembly of this functional lymphatic unit remains unknown. By integrating developmental single-cell profiling, genetic lineage tracing, conditional mouse genetics, and functional assays of lipid absorption, we identify Notch3 as a central organizer of MLC development that coordinates communication between distinct mesenchymal lineages. While Notch3 promotes smooth muscle differentiation within the PDGFRα⁺ lineage, PDGFRβ⁺ lineage cells do not directly contribute to villus smooth muscle. Instead, they function as Notch3-dependent signaling hubs that instruct expansion and differentiation of neighboring PDGFRα⁺ smooth muscle progenitors via paracrine TGFβ signaling. Loss of Notch3 in PDGFRβ⁺ cells disrupts MLC development, impairs intestinal lipid absorption, and causes postnatal growth failure and lethality. Restoration of TGFβ signaling rescues the structural, functional, and survival defects caused by Notch3 loss, identifying TGFβ as a critical downstream effector of the Notch3 pathway. Furthermore, selective inhibition of canonical Notch signaling in the PDGFRβ lineage fails to phenocopy Notch3 deletion, revealing a non-canonical mechanism of Notch3 function in intestinal mesenchymal development. Together, these findings establish PDGFRβ⁺ cells as essential mesenchymal signaling organizers and define a new paradigm in which lineage-specific, non-canonical Notch3 signaling coordinates villus stromal communication to build a functional intestinal lymphatic niche.

ABSTRACT The human heart, originating from the splanchnic mesoderm, is the first functional organ to develop, co‐evolving with the foregut endoderm through reciprocal signaling. Previously, cardioid models offered new insights on cardiovascular cell lineages and tissue morphogenesis during heart development, while mesoderm‐endoderm crosstalk remain incompletely understood. Here, we integrated micropatterned cardioids, CRISPR‐engineered reporter hiPSCs, deep‐tissue imaging, and single‐cell RNA sequencing (scRNA‐seq) to explore synergistic mesoderm‐endoderm co‐development. scRNA‐seq with PHATE trajectory mapping reconstructed lineage bifurcations of mesoderm‐heart and endoderm‐foregut lineages, identifying key cell types in cardiac and hepatic development. Ligand‐receptor interaction analysis highlighted mesodermal cells enriched in non‐canonical WNT, NRG, and TGF‐β signaling, while endodermal cells exhibited VEGF and Hedgehog activity. We found that micropattern sizes influenced cellular composition, cardioid cavitation, contractile functions, and mesoderm‐endoderm signaling crosstalk. The cardioids generated from 600 µm diameter circle patterns showed larger cavity formation resembling early heart chamber formation. Our findings establish micropatterned cardioids as a model for mesoderm‐endoderm co‐development, enhancing our understanding of heart‐foregut synergy during early embryogenesis.

BACKGROUND:Proteins and RNA circulate in plasma and can offer insights into human physiology. Yet, despite their clinical importance, direct comparisons between these analytes remain unexplored. METHODS:Here, we measure and compare plasma cell-free RNA (cfRNA) and protein levels for 263 children diagnosed with inflammatory diseases, specifically either Kawasaki disease (KD) or Multisystem Inflammatory Syndrome in Children (MIS-C), by RNA sequencing (n = 108 KD and n = 47 MIS-C, mean age=4.2 years) and SomaScan proteomics (n = 70 KD and n = 101 MIS-C, mean age=6.8 years). RESULTS:Here we show that cell-free RNA and protein levels are largely uncorrelated across samples (feature-by-sample correlation coefficient 0.052; median feature-level correlation coefficient 0.009). Nonetheless, machine learning models based on either modality distinguish KD from MIS-C with similar high accuracy (median area under the curve greater than 0.93). Analysis of KD subtypes reveals distinct cell-free RNA and protein signatures, with one group showing molecular similarity to MIS-C. CONCLUSIONS:These findings underscore the complementary nature of cell-free RNA and protein profiling and highlight the utility of integrating multiple plasma analytes to improve disease classification and deepen our understanding of complex inflammatory conditions.

The gut microbiome is a highly dynamic ecosystem, yet its temporal organization remains poorly understood because microbiome sampling is typically limited to sparse time points. To overcome this challenge, we developed an automated device to enable continuous fecal sampling from individual mice at minute- to hour-scale resolution. Combining full-length 16S rRNA amplicon sequencing with a limited set of long-read metagenomic references, we economically reconstructed genome- and function-level trajectories at high temporal resolution. Automated hourly sampling over 14 consecutive days enabled phase analysis, revealing collective synchronization of taxa partitioned by carbohydrate utilization strategies between day and night, with microbial taxa and functional genes showing reproducible temporal succession across mice. Perturbations such as cage transfer or antibiotic treatment transiently disrupted this functional synchronization, followed by recovery toward a coherent dynamical state. This system and analytic frameworks will enable us to explore rapid microbiome dynamics in health and disease.

Store-operated calcium entry (SOCE) plays a critical role in regulating intracellular calcium signaling and is essential for immune cell functions. SOCE blockade with the pyrazole derivative BTP2 has been explored as an anti-inflammatory strategy in preclinical models, and Zegocractin (CM4620) is under clinical investigation as a CRAC channel inhibitor with activity in multiple tissues, including immune cells. However, the cell type-specific consequences of SOCE blockade under defined activation contexts remain incompletely understood. Here, we used multiplexed single-cell RNA sequencing to investigate the effects of two prototypic SOCE blockers, BTP2 and CM4620, on polyclonally stimulated, normal human peripheral blood mononuclear cells (PBMCs) in a phytohemagglutinin (PHA)-driven T-cell activation model. The data revealed that SOCE blockade suppressed cytotoxicity-associated transcriptional programs in CD8+ effector T cells and natural killer (NK) cells, restoring them to levels comparable to unstimulated cells. At the same time, SOCE blockade allowed CD4+ regulatory T cells to retain transcriptional signatures associated with immune regulation. These results indicate that, in this experimental model, SOCE blockade dampens cytotoxic programs while maintaining tolerance signatures, suggesting a potential avenue for targeted immune modulation in transplantation and other immune-mediated conditions. SIGNIFICANCE STATEMENT: Store-operated calcium entry (SOCE) is essential for immune activation, but broad immunosuppression can cause significant side effects. Using single-cell transcriptomics in a phytohemagglutinin (PHA)-driven T-cell activation model, we show that SOCE blockade with BTP2 or CM4620 suppresses pro-inflammatory and cytotoxic programs in CD8+ effector T cells and NK cells while preserving tolerance-associated pathways in CD4+ regulatory T cells. These findings suggest that SOCE blockade may provide a more targeted form of immune modulation, warranting future head-to-head comparisons with conventional immunosuppressants. Our results highlight the potential of SOCE blockers to reduce immune-mediated damage while maintaining tolerance, motivating further functional and translational studies in transplantation and other immune-mediated conditions.

Epithelial-mesenchymal plasticity (EMP) is activated in carcinoma cells to drive metastasis and chemoresistance. Recently, we demonstrated that EMP activation results in an immunosuppressive tumor microenvironment and immunotherapy resistance in a syngeneic orthotopic murine model. However, it has yet to be shown whether this is conserved in canine carcinomas. Here, we show that in spontaneous canine mammary carcinomas (CMCs), which share clinical and molecular features with human breast cancers, EMP is linked to the recruitment of immunosuppressive cells. Additionally, we identify that the glycoprotein CD109 is associated with EMP-mediated immunosuppression in canine, murine, and human models. CD109 has been associated with tumorigenicity, but not immunosuppression in cancers of any species. Finally, we identified shared upregulation of immunosuppressive factors across multiple canine carcinomas, including oral squamous cell carcinoma, urothelial carcinoma, and pulmonary carcinoma. These findings demonstrate that EMP is associated with immunosuppression in canine carcinomas, with translational implications for human breast cancers. Studying naturally-occurring canine mammary carcinomas reveals associations between epithelial-mesenchymal plasticity and immunosuppression, as well as upregulation of CD109.

Abstract Large language models can synthesize biomedical knowledge, parse vast amounts of data, and generate code, positioning them as promising tools for biomarker discovery from high-throughput omics data. Here, we benchmark six models from OpenAI, Anthropic, and Google on plasma cell-free RNA datasets spanning three clinical cohorts: Kawasaki disease versus multisystem inflammatory syndrome in children, active tuberculosis versus symptomatic respiratory controls, and myalgic encephalomyelitis/chronic fatigue syndrome versus sedentary controls. We evaluate literature-guided nomination of diagnostic gene panels for downstream machine learning and autonomous construction of end-to-end classifiers from raw count matrices to held-out test predictions. Despite prompt adherence issues, model-nominated panels recapitulate canonical immune pathways and outperform random panels across cohorts, even matching differential gene expression baselines in the tuberculosis cohort. End-to-end automation proves feasible but is model- and task-dependent. One model approaches conventional performance for Kawasaki disease versus multisystem inflammatory syndrome in children, whereas performance decreases for tuberculosis and myalgic encephalomyelitis/chronic fatigue syndrome cohorts. These findings delineate current capabilities and limitations of large language models in diagnostics and open a path for their future use in biomarker discovery.

Finding correlations in spatial gene expression is fundamental in spatial transcriptomics, as co-expressed genes within a tissue are linked by regulation, function, pathway, or cell type. Yet, sparsity and noise in spatial transcriptomics data pose significant analytical challenges. Here, we introduce Smoothie, a pipeline that denoises spatial transcriptomics data with Gaussian smoothing and constructs and integrates genome-wide co-expression networks. Utilizing implicit and explicit parallelization, Smoothie scales to datasets exceeding 100 million spatially resolved spots with fast run times and low memory usage. We demonstrate how co-expression networks measured by Smoothie enable precise gene module detection, functional annotation of uncharacterized genes, linkage of gene expression to genome architecture, and multi-sample comparisons to assess stable or dynamic gene expression patterns across tissues, conditions, and time points. Overall, Smoothie provides a scalable and versatile framework for extracting deep biological insights from high-resolution spatial transcriptomics data.

Viral encephalitis is a debilitating disease that most commonly affects vulnerable populations, including the very young and elderly. Despite its severity, few countermeasures exist due to the structural and immunological complexities of the central nervous system (CNS). To better understand the spatial dynamics of viral spread and the concurrent host immune responses, we used high-resolution spatial transcriptomics to profile reovirus infection in the neonatal mouse brain at 3, 5, and 7 days post-infection. We constructed a comprehensive spatiotemporal atlas of infection, which revealed viral dissemination from sites of cerebrospinal fluid circulation to neighboring brain parenchyma, with enriched infection in the thalamus and midbrain coincident with Slc17a6 (VGLUT2) excitatory neurons. Unbiased spatial gene co-expression network analysis uncovered rich gene lists linked to temporal waves of host immune responses, originating with interferon-stimulated gene modules, followed by myeloid cell infiltration and adaptive cytotoxic T-cell responses at times of peak disease. Furthermore, we identified spatial correlation between viral transcripts and several upregulated host snoRNA-related genes (e.g., Nop58 and Snhg1) with high-confidence, suggesting viral use of host ribosomal modification machinery. We also observed a strong anti-correlation of astrocyte markers with reovirus transcripts, suggesting glial cell disruption. This work provides a high-definition spatial framework to understand interactions between viral infection and host immunity in the brain.

PURPOSE OF REVIEW:Cell-free nucleic acids (cfNAs) in plasma and urine have emerged as noninvasive biomarkers for monitoring kidney transplant health. This review summarizes recent advances in the development of cell-free DNA (cfDNA) and cell-free RNA (cfRNA) assays for immune and infection-related complications, and discusses their potential to enable precision monitoring of allograft health. RECENT FINDINGS:Large prospective multicenter studies have established donor-derived cfDNA as a robust biomarker of acute allograft rejection, with increasing evidence supporting the use of cfDNA for surveillance, prognostication, and integration with complementary molecular and clinical biomarkers. Metagenomic cfDNA assays enable broad detection of bacterial, viral, and fungal pathogens. More recently, cfRNA profiling has emerged as a complementary approach that captures tissue-type and cell-type-specific transcriptional activity, providing molecular insight into immune activation, tissue injury, and disease mechanisms. Urine cfRNA is particularly promising because of its enriched representation of kidney-derived transcripts. SUMMARY:Cell-free nucleic acid assays are reshaping the management of kidney transplant recipients by enabling noninvasive assessment of rejection, infection, and allograft injury. Continued advances in sequencing technologies, computational methods, and multimodal biomarker integration are expected to accelerate their clinical adoption and improve precision care for transplant recipients.

The spatial organization of adaptive immune cells within lymph nodes is critical for understanding immune responses during infection and disease. Here, we introduce AIR-SPACE, an integrative approach that combines high-resolution spatial transcriptomics with paired, high-fidelity long-read sequencing of T and B cell receptors. This method enables the simultaneous analysis of cellular transcriptomes and adaptive immune receptor (AIR) repertoires within their native spatial context. We applied AIR-SPACE to mouse popliteal lymph nodes at five distinct time points after Vaccinia virus footpad infection and constructed a comprehensive map of the developing adaptive immune response. Our analysis revealed heterogeneous activation niches, characterized by Interferon-gamma (IFN-γ) production, during the early stages of infection. At later stages, we delineated sub-anatomical structures within the germinal center (GC) and observed evidence that antibody-producing plasma cells differentiate and exit the GC through the dark zone. Furthermore, by combining clonotype data with spatial lineage tracing, we demonstrate that B cell clones are shared among multiple GCs within the same lymph node, reinforcing the concept of a dynamic, interconnected network of GCs. Overall, our study demonstrates how AIR-SPACE can be used to gain insight into the spatial dynamics of infection responses within lymphoid organs.

Breast cancer bone metastasis is a major cause of mortality in patients with advanced breast cancer. Although decreased mineral density is a known risk factor for bone metastasis, the underlying mechanisms remain poorly understood because studying the isolated effect of bone mineral density on tumor heterogeneity is challenging with conventional approaches. Moreover, mineralized biomaterials are commonly utilized for clinical bone defect repair, but how mineralized biomaterials affect the foreign body response and wound healing is unclear. Here, we investigate how bone mineral affects tumor growth and microenvironmental complexity in vivo by combining single-cell RNA-sequencing with mineral-containing or mineral-free decellularized bone matrices. We discover that the absence of bone mineral significantly influences fibroblast and immune cell heterogeneity, promoting phenotypes that increase tumor growth and alter the response to injury or disease. Importantly, we observe that the stromal response to bone mineral content depends on the murine tumor model used. While lack of bone mineral induces tumor-promoting microenvironments in both immunocompromised and immunocompetent animals, these changes are mediated by altered fibroblast phenotype in immunocompromised mice and macrophage polarization in immunocompetent mice. Collectively, our findings suggest that bone mineral density affects tumor growth by impacting microenvironmental complexity in an organism-dependent manner.

Mouse lemurs (Microcebus spp.) are an emerging primate model organism, but their genetics, cellular and molecular biology remain largely unexplored. In an accompanying paper1, we performed large-scale single-cell RNA sequencing of 27 organs from mouse lemurs. We identified more than 750 molecular cell types, characterized their transcriptomic profiles and provided insight into primate evolution of cell types. Here we use the generated atlas to characterize mouse lemur genes, physiology, disease and mutations. We uncover thousands of previously unidentified lemur genes and hundreds of thousands of new splice junctions including over 85,000 primate splice junctions missing in mice. We systematically explore the lemur immune system by comparing global expression profiles of key immune genes in health and disease, and by mapping immune cell development, trafficking and activation. We characterize primate-specific and lemur-specific physiology and disease, including molecular features of the immune program, lemur adipocytes and metastatic endometrial cancer that resembles the human malignancy. We present expression patterns of more than 400 primate genes missing in mice, many with similar expression patterns to humans and some implicated in human disease. Finally, we provide an experimental framework for reverse genetic analysis by identifying naturally occurring nonsense mutations in three primate immune genes missing in mice and by analysing their transcriptional phenotypes. This work establishes a foundation for molecular and genetic analyses of mouse lemurs and prioritizes primate genes, isoforms, physiology and disease for future study.

Embryonic heart development depends on coordinated interactions between cellular programs, molecular signaling, and biomechanical forces, yet how mechanical cues shape cellular and molecular pathways remains incompletely understood. We perturbed cardiac blood flow by partial left or right atrial ligation (LAL/RAL) in chick embryos, generating chamber-specific hemodynamic gain- or loss-of-function states. Using single-cell and unbiased, high-resolution spatial transcriptomics, we generated a spatiotemporal atlas of flow-dependent tissue development, enabling systematic investigations of bidirectional interactions between blood-flow mechanics and tissue development. Spatially resolved analyses recapitulated key features of normal morphogenesis including regional maturation and the cellular neighborhood. We further revealed flow-specific remodeling across molecular, cellular, and architectural levels. Altered flow induced LOX-expressing cardiomyocyte and endocardial states, disrupted ventricular layer organization, and delayed maturation, alongside transient metabolic and ion-transport adaptations. Together, these findings define how redistributed blood flow reshapes developing cardiac tissues and provide a framework for studying flow-dependent remodeling in morphogenesis and malformation.

Introduction:Immune checkpoint inhibitor-associated acute interstitial nephritis (ICI-AIN) is the most common finding on histopathology among patients with ICI-associated acute kidney injury (ICI-AKI). Patients with ICI-AIN often have T cell-dominant infiltration of the kidney and high tissue levels of CXCR3 ligands like CXCL9, 10, and 11; however, the mechanisms of inflammation in ICI-AIN are not well-understood. Methods:We applied a sub-cellular spatial transcriptomics platform (Xenium Prime 5K) to compare the cellular composition of kidney biopsy tissue from patients with ICI-AIN with ICI-treated patients with acute tubular necrosis (ICI-ATN). Results:Across 8 kidney biopsy specimens (4 with ICI-AIN, 4 with ICI-ATN), we analyzed 332,000 cells, comprising kidney parenchymal cells and infiltrating immune cells. Using a spatially-aware cellular neighborhood-based classification, we identified cellular niches corresponding to each part of the nephron, in addition to unique fibrotic and inflammatory niches. Gene pathway analysis identified interferon-gamma (IFN-γ)/STAT1 signaling as strongly increased in ICI-AIN compared to ICI-ATN. While all inflammatory niches were overrepresented in ICI-AIN, CD8+ T cell infiltration and proinflammatory myeloid cells were the dominant immune niches. Spatial niche crosstalk analysis revealed that CD8+ T cell-derived IFN-γ likely induced a proinflammatory program in myeloid cells, with increased production of CXCL9, 10, and 11. Furthermore, IFN-γ signaling in ICI-AIN was associated with reduced oxidative phosphorylation in kidney tubular niches. Conclusions:Spatial transcriptomics reveal novel insights into key differences in the pathophysiology of ICI-AIN versus ICI-ATN. IFN-γ-producing CD8+ T cells are likely key drivers of ICI-AIN and should be investigated as future therapeutic targets.

BACKGROUND:There is increasing interest in the use of circulating cell-free RNA (cfRNA) in plasma as an analyte for diagnosing and monitoring disease. While it is known that cfRNA can also be isolated from urine, the diagnostic potential of urine cfRNA, particularly relative to plasma cfRNA, remains underexplored. METHODS:Matched plasma and urine were collected from hematopoietic stem cell transplant (HSCT) recipients (n = 24), immune-checkpoint-inhibitor (ICI) recipients with or without acute kidney injury (AKI) (n = 46), and healthy volunteers (n = 5), yielding 297 samples. Unbiased cfRNA sequencing was performed, followed by comparison of molecular diversity, tissue and cellular origin, and diagnostic performance for systemic (HSCT) and renal (AKI) complications. RESULTS:Urine and plasma cfRNA displayed distinct molecular composition and cellular origin across all groups. In HSCT, pronounced changes in plasma cfRNA were detected during the course of treatment, while urine cfRNA changes were minimal. Conversely, when comparing ICI recipients with and without AKI, cfRNA signatures indicative of disease and AKI etiology were observed in urine but not in plasma. These urine-derived signatures included injury markers and immune transcripts consistent with localized renal inflammation. CONCLUSIONS:This study reveals the distinct origin and diagnostic utility of plasma and urine cfRNA and suggests urine cfRNA is a promising analyte to monitor kidney injury, especially in the context of AKI following ICI treatment.

Macrophages serve as sentinels at the intestinal surface, responding to organismal cues to drive proinflammatory or tolerogenic responses. To date, studies of combinations of these cues do not fully capture the heterogeneity of macrophage responses. To address this gap, we performed multiplexed single-cell RNA sequencing on 74,476 human monocyte-derived macrophages following exposure to 15 bacteria, mostly commensals. We observe clusters that appeared only after macrophage exposure to bacteria, and transcriptional responses within each cluster varied by species and Gram status. The proportion of each cluster also varied among exposure conditions. Macrophages exposed to defined combinations of organisms revealed that Fusobacterium nucleatum drives inflammatory responses, whereas Mediterraneibacter gnavus tempers them. Overall, our results show that macrophages distinguish between commensal organisms, relevant to intestinal diseases characterized by altered microbiome compositions. This sequencing dataset will be a useful resource to probe human macrophage response to a broad range of bacteria.