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Biology subjects

Yu, X.

Publications and source records attributed to Yu, X..

At least 91 records · Page 5Linked to original sources

Toward Computationally Complete Spatial Omics

Multimodal spatial omics has transformed biology by mapping molecular complexity within intact tissues, yet current technologies remain limited in the number of modalities measured simultaneously and often produce lower-quality data than single-modality assays. We present COSIE, a computational framework that generates high-resolution, multilayered molecular landscapes across tissue sections, individuals, and platforms. COSIE integrates histology, epigenome, transcriptome, proteome, and metabolome into a unified representation. Applied to 12 datasets spanning 10 spatial technologies, eight modalities, and nine tissue types, ranging from thousands of spots to millions of cells, COSIE outperforms existing methods. It resolves tissue structures, enhances noisy measurements, predicts unmeasured modalities, and captures dynamic processes. In human tumors, COSIE identifies invasive subregions linked to clinical outcomes and predicts spatial gene expression in TCGA samples using only histology images. By transforming fragmented data into comprehensive spatial maps, COSIE advances computationally complete spatial omics and the creation of digital tissue twins for biomedicine.

genomics↗

Multiscale confidence quantification for virtual spatial transcriptomics with UTOPIA

Virtual spatial transcriptomics (ST) methods predict gene expression or cell types from histology images, extending molecular readouts beyond the limited regions or samples directly measured by ST platforms. However, the statistical reliability of these predictions remains unclear. Here, we present UTOPIA, a model-agnostic framework for multiscale confidence quantification in virtual ST. UTOPIA assigns statistically calibrated confidence scores to predictions across spatial resolutions and biological granularities, ranging from single genes to metagenes and from specific cell types to broader cell classes. UTOPIA controls false discovery rates for detecting genes, metagenes, or cell types while accounting for local tissue context. We show that prediction confidence depends critically on both spatial resolution and biological granularity, with reliable inference often emerging only at coarser, biologically meaningful scales. Across multiple ST platforms and in both in-sample and out-of-sample settings, UTOPIA enhances interpretability, prevents false biological conclusions, and enables more trustworthy downstream analyses of virtual ST.

genomics↗

Genomic language models improve cross-species gene expression prediction and accurately capture regulatory variant effects in Brachypodium mutant lines

Predicting gene expression from cis-regulatory DNA sequences at the promoter and terminator regions is a central challenge in plant genomics. This capability is also a prerequisite for assessing the effects of regulatory mutations on gene expression. Here, we developed deep learning sequence-to-expression (S2E) models that leverage context-aware sequence embeddings from the PlantCaduceus genomic language model instead of one-hot encoding of sequences, to predict gene expression across 17 plant species. To further improve predictions, we integrated chromatin accessibility data as auxiliary regulatory features. First, we evaluated our models to predict gene expression on unseen gene families via cross-validation, demonstrating our models prediction accuracy across all species outperforms PhytoExpr, the current state-of-the-art (SOTA) S2E model in plants (Pearson R=0.82 vs. R=0.74). We then validated variant effect predictions using an experimental dataset across 796 Brachypodium mutant lines, specifically designed to test predictions at single-base resolution. Our models outperformed SOTA S2E models in predicting between-gene expression differences (regression coefficient {beta}=0.78 vs. {beta}=0.57). Remarkably, they also accurately predicted the effects of single-nucleotide mutations on within-gene expression, while SOTA S2E models showed only weak associations (regression coefficient {beta}=0.38 vs. {beta}=0.08). Our results demonstrated the value of context-aware DNA sequence embeddings for predicting regulatory variant effects in plants. They also reveal a persistent accuracy gap in S2E models when moving from between-gene to allelic variation, a challenge that needs to be addressed in future S2E studies.

bioinformatics↗

Endocardial TIE1 synergizes with TIE2 to regulate the atrial internal muscular network assembly

Atrial cardiomyopathy is characterized by altered atrial structures, yet its underlying genetic basis remains inadequately explored. TIE1 mutations are reported in lymphedema patients, but whether they exhibit cardiac defects alongside lymphatic abnormalities remains unknown. Here, single-cell RNA sequencing showed high Tie1 and Tek expression in atrial endocardial cells. TIE1 deficiency severely disrupted atrial morphogenesis, with only minor ventricular defects. Bulk RNA-seq showed reduced transcripts for endothelial development and cardiac trabeculation in Tie1 mutants. Separate RNA-seq analysis of the atria and ventricles further confirmed these findings, revealing a more pronounced downregulation of trabecular genes, including Tek, in the atria upon Tie1 loss. Endothelial deletion of Tek impaired trabeculation, particularly in atria. Consistently, Tie1 loss combined with a single null Tek allele disrupted both atrial and ventricular trabeculation. Strikingly, atrial morphogenesis defects appeared within 48 hours of induced endothelial Tie1 loss coupled with Tek heterozygous deletion, implying a critical endocardial role in organizing the atrial muscular network. The synergy of TIE1 and TIE2 in remodeling atrial trabeculae was confirmed postnatally, whereas TIE1 insufficiency alone had no effect. Together, TIE1 is differentially required for atrial versus ventricular development, acting synergistically with TIE2 to regulate endocardial cell-coordinated assembly of atrial internal muscular network.

developmental biology↗

A Dual-Phase Strategy to Integrate the VITEK MS RUO Database into Routine Clinical Practice: From Validation of Analytical Performance to Implementation of an Automated Workflow

BackgroundMatrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is pivotal in clinical microbiology. The VITEK MS Research Use Only (RUO) database offers broader species coverage, yet its clinical adoption is hindered by insufficient performance validation against the approved in vitro diagnostic (IVD) database and inefficient manual operational workflows. ObjectiveThis two-phase study first aimed to develop and evaluate an automated integrated workflow to enhance laboratory efficiency and diagnostic capability. MethodsThe RUO databases two-tier identification architecture was utilized and in-house automated relay software was developed to parse IVD results and fully automate RUO reanalysis. Phase 1 (Mar 2021-Jun 2022) involved parallel manual testing of 2,432 isolates with both databases to analyze concordance and supplementary performance. Phase 2 (Jul-Nov 2022) prospectively incorporated 3,954 isolates to implement and assess the "IVD screening - automated RUO reanalysis" workflow. ResultsPhase 1 demonstrated high RUO-IVD concordance (95.7% species/genus agreement). The RUO database correctly identified 98.9% of isolates and provided valid supplementary identification for 84.4% (108/128) of IVD-failed cases, with Tier 2 contributing 28.9%. Phase 2 revealed that the integrated workflow increased the overall identification rate from 95.5% to 98.7%, with Tier 2 contributing an additional 14.5%. The automated software reduced reanalysis turnaround time by > 75%, saving consumables and labor. ConclusionThe VITEK MS RUO database is a reliable and complementary tool to the IVD database. Integration with automated software creates an efficient, compliant clinical workflow, providing a practical model to enhance pathogen identification for infectious disease management. IMPORTANCEThe present study bridges the validation-to-application gap for the VITEK MS RUO database. We confirm its high concordance (95.7%) and complementary value to the IVD database, quantify the impact of manual workflow inefficiency and introduce an automated software solution. The strategy highlights the key role of Reference Spectra (Tier 2) in expanding coverage and simultaneously improves diagnostic efficacy ([~]99% ID rate), operational efficiency (> 75% time saved) and cost-effectiveness, offering a practical model to accelerate pathogen reporting and to guide therapy.

microbiology↗

Single-nucleus RNA sequencing reveals cell type-specific responses to heat stress in bovine mammary gland

BackgroundHeat stress (HS) poses a major challenge to the dairy industry by reducing milk production, yet its cell type-specific effects in the bovine mammary gland remain incompletely defined. In this study, we recorded production traits and collected mammary biopsies from cows under thermoneutral (TN), HS, and pair-fed (PF) conditions. ResultsClinical measurements confirmed HS-induced physiological alterations. Compared with TN cows, HS cows exhibited reduced dry matter intake (DMI), milk yield, and yields of fat, protein, and lactose, along with increased water intake and milk urea nitrogen. The use of PF controls indicated that decreased DMI accounted for 45% of the milk-yield reduction, whereas direct HS effects accounted for the remaining reduction. We applied single-nucleus RNA-seq (snRNA-seq) on mammary biopsies to generate cell-resolved HS responses. We identified 14 distinct cell clusters, including epithelial, immune, and stromal populations. Under the TN condition, casein genes (e.g., CSN1S1, CSN2) were broadly expressed across luminal cells but were attenuated under HS, whereas luminal alveolar cells showed relative upregulation. Heat shock protein genes were strongly induced by HS, primarily in epithelial clusters. Gene-set enrichment analyses revealed increased ribosomal activities across HS-responsive clusters and enrichment of protein folding and metabolic pathways in luminal alveolar cells, suggesting elevated proteostasis demands under stress. Pseudotime analysis positioned luminal cells along a progenitor-to-secretory trajectory under TN, accompanied by increased casein gene expression, whereas under HS, mature luminal cells shifted toward a homeostasis regulatory state. Cell-cell communication analysis demonstrated HS-induced remodeling of interepithelial signaling, including altered ERBB4-mediated signaling from luminal hormone-sensing to alveolar lineages. Finally, transcription factor activity profiling highlighted cell type-specific HS-activated regulators and their downstream target genes. ConclusionsTogether, this cell type-resolved atlas delineates how HS alters bovine mammary epithelial function, developmental state, and intercellular crosstalk. These findings point to proteostasis pressure, disrupted signaling pathways, and rewired regulatory networks as mechanistic contributors to reduced lactational performance under HS, offering insights for improving heat resilience in dairy cattle.

genomics↗

Leveraging ONT move table values for signal aware variant calling

Oxford Nanopore Technologies (ONT) sequencing enables long-range haplotype phasing and contiguous genome assembly but still exhibits elevated error rates that challenge small variant calling, particularly for insertions and deletions (Indels). While raw electrical signals contain rich information, existing signal-aware methods require computationally intensive processing of large signal files. Here, we present Clair3 v2, a method that leverages the ONT move table--a lightweight byproduct of basecalling that maps signal events to nucleotide positions--to improve variant calling accuracy. Clair3 v2 builds upon Clair3 and integrates signal-level dwelling time to significantly enhance variant calling performance. We also propose a genome position based circular buffer to incorporate dwelling time with minimal computational overhead. Benchmarking across six Genome in a Bottle samples demonstrates substantial improvements in variant calling accuracy. With HAC basecalling, Clair3 v2 achieves a mean SNP F1-score of 97.69% at 10x depth (compared to 96.45% for baseline Clair3), and Indel F1 scores improved from 64.27% to 76.70%, while gains persisted at higher depths. The benefits were most pronounced for longer Indels and in complex genomic regions, where Indel F1 scores in long homopolymer regions improved from 14.3% to 45.2%. Benchmark results across various basecalling modes, samples, and coverage settings outperformed Clair3 baselines and other methods, including DeepVariant and Dorado Variant, and demonstrate the significant benefits of Clair3 v2. Furthermore, Clair3 v2 incurs negligible runtime compared to standard Clair3, making it practical for routine use.

bioinformatics↗

Neural Activity Related Sodium (NARS) fMRI Resolves Millisecond Neuronal Dynamics in the Rodent Cortex

Brain-wide, noninvasive methods that directly resolve neuronal activity on millisecond timescales are still lacking in neuroimaging. Hemodynamic fMRI (1H-based) provides whole-brain maps of activity, yet its vascular origin creates spatial and temporal displacements from neuronal events that complicate interpretation, especially in disease conditions where neurovascular coupling is altered. Here, we developed an ultrafast 23Na fMRI platform at 14 T that combines a reshuffled k-t 3D gradient echo readout (TR/TE, 10ms/1ms) with an implantable RF coil and respiration-gated acquisition. This configuration provides the sampling rate and SNR needed to probe quadrupolar T2*-weighted single quantum sodium dynamics on the neuronal timescale. Across rats and mice, somatosensory forepaw stimulation produced a localized 23Na signal decrease of ~2-3% in the FP-S1, peaking ~10-30 ms post-stimulus. The activity pattern is well matched with conventional BOLD-fMRI maps acquired in the same animals. Trial-by-trial measurements during simultaneous iGluSnFR glutamate fiber photometry demonstrated that larger evoked glutamate transients coincided with larger NARS decreases, supporting a neuronal origin of the NARS contrast. We interpret the negative NARS response as a transient activity-dependent redistribution of sodium ions toward restricted, protein-rich microdomains, where more restricted rotational dynamics may accelerate T2*short decay and produce a 2-3% signal decrease without requiring large changes in bulk sodium concentration. Together, these results establish neural activity-related sodium (NARS) fMRI as a viable approach for direct, mesoscale neuronal mapping with MRI at millisecond resolution. Graphical AbstractA reshuffled k-t 3D gradient echo (GRE) readout with an implantable figure-8 RF coil and respiration-gated trials captures a ~2-3% negative 23Na response peaking 10-30 ms after forepaw stimulation in the FP-S1. NARS fMRI responses co-localize with BOLD-fMRI and scale with iGluSnFR glutamate transients, consistent with activity-dependent shifts toward short-T2* sodium microenvironments. Table of Contents (TOC) BlurbYu et al. introduce NARS-fMRI, an ultrafast 23Na method that resolves millisecond neuronal dynamics in rodent FP-S1. The negative sodium response (10-30 ms) co-localizes with BOLD and correlates with glutamate photometry, supporting a direct neuronal origin.

biophysics↗

High spatial resolution 23Na-MRI for ischemic brain injury detection

High spatial resolution sodium (23Na) imaging of brain lesions remains challenging due to the intrinsically low signal-to-noise ratio (SNR) of 23Na-MRI compared with conventional proton (1H) MRI. In this study, we established a high-resolution 23Na-MRI platform based on 14 T preclinical scanner using a dual-tuned head-implanted RF coil. This configuration enables the acquisition of 1H-based T2-weighted anatomical and diffusion-weighted imaging (DWI), as well as 23Na-MRI, from the same animal. Brain-wide 23Na-MRI with 300x300 {micro}m2 in-plane resolution was performed within the first 4 hours after acute middle cerebral artery occlusion (MCAO) induced ischemic stroke induction. Hyperintense 23Na-MRI signals were observed in the ischemic brain regions, presenting a contrast-to-noise ratio (CNR) that exceeded that of T2-weighted images. Infarct regions can be well-identified in the elevated 23Na signal, which is spatially consistent with regions of reduced apparent diffusion coefficient (ADC) values, indicating water restriction in the ischemic core. This work established implanted double-tuned 1H/23Na RF coils as a powerful approach for high-resolution 23Na-MRI readout, facilitating the early detection of ischemic brain injury.

neuroscience↗

Detection of Somatic Point Mutations Directly from Spatial Transcriptomics Enables in vivo Spatiotemporal Lineage Tracing

Spatial transcriptomics reveals tissue organization but lacks in vivo lineage-tracing methods applicable to humans. We introduce SpaceTracer, a computational framework that accurately detects somatic single-nucleotide variants (SNVs) directly from spatial transcriptomics data. By leveraging naturally occurring somatic SNVs, SpaceTracer reconstructs cellular phylogenies within native tissue architecture, enabling the mapping of lineage spread, migration, lineage-coupled expression changes and lineage-aware local interactions. Applied to human cutaneous squamous cell carcinoma, it traced tumor initiation and progressions, uncovered widespread pre-invasive migration of dedifferentiated epithelial cells and characterized mutant B cells migrating from tertiary lymphoid structures (TLS) into the tumor boundary. The framework also reconstructed developmental lineages across multiple tissues and identified tissue-resident mutant immune cells. SpaceTracer thus provides a perturbation-free platform for high-resolution spatiotemporal lineage tracing, offering a transformative tool for elucidating complex biological systems--especially tumor-immune ecosystems--with direct implications for advancing cancer immunotherapy.

bioinformatics↗

Unravelling genome-wide mosaic microsatellite mutations at single-cell resolution

Short tandem repeats (STRs), or microsatellites, are highly mutable genomic elements that modulate gene regulations and are implicated in a range of human diseases. However, detecting mosaic STR mutations at single-cell resolution remains challenging due to both technical and biological complexities. To address this, we developed BayesMonSTR, a robust algorithm that enables accurate detection of mosaic STR mutations. Using this tool in single-cell analysis of human tissues, we reveal an accumulation of longer mosaic STR insertions and deletions (indels) in aging mitotic and post-mitotic cells. Strikingly, prefrontal cortex (PFC) neurons accumulate a higher burden of STR mutations than B cells or lung epithelium, with aged neurons exhibiting a particularly pronounced increase in longer STR deletions. These mutations are enriched at transcription start sites (TSSs) and active enhancers of highly expressed genes. Our work establishes a foundation for genome-wide, hypothesis-free discovery of disease-associated mosaic STR mutations and reveals a previously unexplored landscape of mosaic STR variation in development and aging.

bioinformatics↗

Characterizing the metabolomes of microglia, astrocytes, and neurons in aging and Alzheimer's brains

Neurons and glia are distinct in their morphology, development, and function, possessing unique transcriptomes and proteomes, but little is known about their metabolomes. The challenge of brain cell metabolic profiling is to obtain a large number of cells for reliable analysis. Here, we purified microglia, astrocytes, and neurons from mouse brains, identifying >70 metabolites through targeted metabolomics and 9,854 metabolite features via untargeted metabolomics. We systematically characterized cell type-enriched metabolites and metabolic pathways, revealing an enrichment of glutathione (GSH) and polyamine metabolism in microglia. This enrichment was validated in vivo and showed significant decreases with aging and in an Alzheimers disease (AD) model. Notably, GSH and polyamine metabolism correlated strongly with chemokine-related gene expression. Disrupting the GSH pathway in microglia resulted in downregulation of chemokine-related genes, aberrant morphogenesis, and {beta}-amyloid deposition. Our results provide a valuable resource (https://metabolismocean.org/braincell) for metabolic studies related to aging, AD, and other neurological diseases.

neuroscience↗

HistoSweep enables cellular-resolution tissue quality control for gigapixel images in digital pathology and spatial omics

High-resolution histology images are indispensable for pathology and increasingly serve as the structural backbone for spatial omics. Yet whole-slide images (WSIs) frequently contain artifacts, acellular voids, and background regions that, when included in computational workflows, introduce noise, degrade model accuracy, and compromise biological interpretation. Existing tools provide only coarse foreground-background separation, leaving a gap in fine-grained quality control (QC). Here we present HistoSweep, a scalable framework that generates morphology-aware tissue masks at cellular resolution. By integrating density filtering, texture descriptors, and adaptive thresholding, HistoSweep systematically removes non-informative tissue regions while preserving biologically meaningful microstructures. It processes billion-pixel WSIs in minutes on standard CPUs, requiring no GPU acceleration, and is deployable across research and clinical settings. Across 25 WSIs spanning distinct tissues, disease states, and spatial omics platforms, HistoSweep consistently outperformed existing methods. It enhanced visualization and segmentation, improved virtual cell type predictions, and safeguarded spatial transcriptomics integrity by detecting transcript leakage and transcript-histology misalignment. By enabling fine-grained, scalable QC, HistoSweep provides a foundational preprocessing step for reliable and reproducible digital pathology and spatial omics analyses.

bioinformatics↗

CCycDB: an integrative knowledgebase to fingerprint microbially mediated carbon cycling processes

Microorganisms play essential roles in mediating biogeochemical cycling of carbon across Earths ecosystems. Understanding the processes and underlying mechanisms for microbially mediated carbon cycling is therefore critical for advancing global ecology and climate change research. To comprehensively depict these complex biogeochemical processes, we developed CCycDB, a knowledge-based functional gene database, to accurately fingerprint microbially-mediated carbon cycling pathways and gene families, particularly from shotgun metagenomes. The CCycDB database comprises 4,676 gene families classified into six major functional categories, further structured into 45 level-1 and 188 level-2 sub-categories, encompassing a total of 10,991,724 high-quality reference sequences. Validation using both synthetic and real-world datasets demonstrated that CCycDB outperforms existing orthology databases in terms of accuracy, coverage and specificity. By directly targeting carbon-cycling functional gene families, CCycDB provided promising routines to reconstruct both functional gene and taxonomic profiles associated with microbially mediated carbon cycling. Application of CCycDB to shotgun metagenomes from diverse and complex ecosystems revealed pronounced habitat-specific differences in carbon cycling processes and their associated microbial taxa. Collectively, CCycDB provides a powerful and reliable tool for profiling carbon cycling processes from both functional and taxonomic perspectives in complex ecosystems. CCycDB is accessible at https://ccycdb.github.io/. Impact StatementThe microbially mediated carbon cycling processes are the most complex biogeochemical processes in the Earths biosphere, playing profound regulatory roles on global climate changes. A key bottleneck in linking microbial communities to global change is the lack of integrated tools for comprehensive carbon cycle profiling. Here, we present CCycDB, a tool that serves a dual purpose--first being a reference database that obtains functional gene and taxonomic profiles and functioning as a customized routine for efficiently aligning sequences and querying associated functional information. CCycDB enables researchers to accurately link microbial community dynamics to carbon cycling and transforming pathways, thereby advancing integrated global change studies with microbes and ecological research via complex metagenomic datasets.

microbiology↗

Multifaceted Functional Complexity of SARS-CoV-2 Helicase Nsp13 Underlies Its Integrated Motor and Remodeling Activities

SARS-CoV-2 nonstructural protein 13 (Nsp13) is a superfamily 1 helicase essential for viral replication. Although its canonical ATP-dependent unwinding activity is well established, the broader functional repertoire of Nsp13 remains unclear. Here, we show that Nsp13 encodes a high degree of complexity by acting as a tunable nucleic acid remodeler that integrates motor and non-motor activities within a single protein. Nsp13 operates in multiple mechanistically distinct regimes, including a canonical ATP-dependent helicase mode and a Mg{superscript 2}-primed, ATP-independent remodeling state capable of destabilizing short duplexes, hairpins, and G-quadruplexes. Mg{superscript 2} binding allosterically stabilizes a compact RecA1-RecA2 configuration, priming the enzyme for ATP-independent remodeling. Unwinding polarity is substrate-dependent, with duplexes supporting bidirectional remodeling, whereas G-quadruplexes are preferentially resolved in the 5'[->]3' direction. Beyond strand separation, Nsp13 also exhibits robust strand annealing and nucleic acid chaperone activities. Cofactors, substrate topology, and enzyme concentration dynamically regulate these activities. Together, our findings establish Nsp13 as a highly integrated nucleic acid remodeling system and reveal how a single viral helicase switches between motor-driven and remodeling-dominated states to meet the structural demands of replication and transcription.

biochemistry↗

Smooth Muscle Dysfunction Drives Cerebrovascular Reserve Failure and End-Organ Brain Injury

BackgroundFailure of cerebrovascular reserve is a fundamental determinant of ischemic vulnerability, yet the mechanisms by which vascular smooth muscle dysfunction compromises reserve and predisposes the brain to injury remain incompletely defined. We therefore tested whether a pathogenic smooth muscle mutation produces a baseline failure of cerebrovascular reserve sufficient to render the brain vulnerable to hypoperfusion, even in the absence of fixed arterial occlusion. MethodsWe examined cerebrovascular structure, hemodynamics, and reserve in a genetically defined mouse model of ACTA2-associated multisystemic smooth muscle dysfunction syndrome with systemic or brain-restricted expression of the mutant allele. Cerebral artery morphology was assessed using magnetic resonance angiography and black ink angiography. Vascular smooth muscle phenotype was evaluated by immunohistochemistry and proliferation assays. Blood pressure reactivity and cerebral blood flow (CBF) were measured simultaneously using femoral arterial catheterization and laser speckle flowmetry during vasoactive challenges and controlled hypotension. Cerebrovascular stress responses were tested using unilateral common carotid artery occlusion. Downstream brain effects were assessed by histology, resting state functional connectivity imaging, and behavioral testing. ResultsImpaired smooth muscle contractility drove rectification and narrowing of major cerebral arteries, downregulation of contractile markers, and increased vascular cell proliferation. These structural changes produced a distinct physiological phenotype: mutant mice exhibited blunted vasoreactivity, diminished spontaneous vasodynamic activity, and a downward shift in the blood pressure-CBF relationship across a wide range of arterial pressures, consistent with loss of cerebrovascular reserve. As a result, CBF was reduced at baseline and could not be maintained during hypotension or acute vascular stress. During carotid occlusion, mutant mice showed impaired compensatory perfusion, greater physiological instability, and worse behavioral outcomes. Chronic reserve failure coincided with white matter loss, reduced neuronal density, disrupted large-scale functional connectivity, and deficits in locomotion, anxiety-related behavior, and working memory. ConclusionsPathogenic smooth muscle dysfunction caused by ACTA2 mutation produces a baseline failure of cerebrovascular reserve that renders the brain vulnerable to hypoperfusion and stress-induced ischemic injury. These findings establish cerebrovascular reserve failure as a central physiological mechanism linking vascular dysfunction to end-organ brain injury and identify reserve preservation as a critical, potentially actionable determinant of brain health in hypotension-prone vascular disease. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABS- ACTA2 smooth muscle dysfunction produces baseline cerebrovascular reserve impairment, with reduced cerebral blood flow and a downward-shifted pressure-flow relationship in the absence of critical large-vessel occlusion. - Vascular tone dysregulation is coupled to end-organ brain injury, including white matter and neuronal loss, disrupted functional connectivity, and behavioral deficits. - The results support complementary disease mechanisms in ACTA2 vasculopathy: baseline reserve limitation and injury-provoked occlusive remodeling. Clinical Implications- Patients with ACTA2 vasculopathy may be vulnerable to ischemic brain injury during hypotension or systemic stress despite the absence of critical stenosis or occlusion on routine imaging. - Peri-procedural and acute-care management should emphasize preserving perfusion pressure and cerebrovascular reserve (e.g., during anesthesia, dehydration, or systemic illness). - More broadly, cerebrovascular reserve is a clinically relevant, potentially modifiable determinant of brain health in hypotension-prone vasculopathies and conditions characterized by impaired vascular reactivity.

physiology↗

MAPKAP Kinase 2 Orchestrates Memory T Cell Inflation in Cytomegalovirus Infection

Memory T cell inflation is a distinctive immunological phenomenon observed during persistent viral infections, such as Cytomegalovirus (CMV). Unlike conventional memory T cell responses, which contract after infection resolution, a subset of CMV-specific T cells undergoes a progressive and sustained expansion, termed "inflation", which is thought to be critical for long-term immune surveillance. The molecular mechanisms that govern memory T cell inflation remain incompletely understood, yet they are pivotal for understanding immune persistence and designing strategies against chronic viral infections. In this study, we investigate the role of MAP kinase-activated protein kinase 2 (MK2), a key downstream effector of p38 MAPK signaling, in regulating T cell responses during murine CMV (MCMV) infection. Using MK2 knockout (MK2-KO) mice, we demonstrate that MK2 deficiency alters the dynamics of MCMV-specific CD8 T cell responses without impairing viral control or tissue replication. MK2 deficiency led to a reduction in non-inflationary MCMV-specific CD8 T cells during the acute phase, followed by enhanced expansion of inflationary CD8 T cell subsets during persistence. Furthermore, MK2-KO mice exhibited impaired effector differentiation, as evidenced by decreased expression of the terminal differentiation marker KLRG1 on MCMV-specific CD8 T cells. Collectively, these findings identify MK2 as a pivotal regulator of CD8 T cell magnitude, kinetics, and phenotype during both acute and chronic MCMV infection. By elucidating the role of MK2 in the regulation of memory T cell inflation, this study provides new mechanistic insight into immune regulation with implications for vaccination, chronic infection, and immune aging. Graphical abstractThe graphical abstract was created using BioRender (https://biorender.com/). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/699974v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@140d602org.highwire.dtl.DTLVardef@1a23691org.highwire.dtl.DTLVardef@ac75b6org.highwire.dtl.DTLVardef@640d68_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

Targeting PI3Kβ-dependent cancer with a novel small molecule inhibitor, GT220

PI3K{beta} is a critical oncogenic driver in cancers harboring PTEN loss or PIK3CB alterations, yet effective and selective PI3K{beta}-targeted therapies remain elusive. Here, we report the development and preclinical characterization of GT220, a highly selective and potent small-molecule PI3K{beta} inhibitor developed through integrated artificial-intelligence-driven design with medicinal chemistry and pharmacologic optimization. GT220 exhibits exceptional biochemical selectivity for PI3K{beta}, binding with sub-nanomolar affinity and with minimal activity against other class I PI3K isoforms or the broader protein kinome. In cellular models, GT220 potently suppresses AKT phosphorylation and selectively inhibits viability of PTEN-deficient cancer cells, while sparing PTEN/PIK3CB wild-type and PI3K-dependent cells. In vivo, GT220 achieves a favorable tumor exposure with sustained PI3K{beta} pathway inhibition and demonstrates robust antitumor efficacy and good tolerability in PTEN-deficient breast cancer xenograft models. In contrast, GT220 shows no antitumor activity or pathway inhibition in PTEN-wild-type or PI3K-dependent tumors, underscoring its context-dependent mechanism of action. Collectively, these findings establish GT220 as a promising next-generation PI3K{beta} inhibitor and provide a strong preclinical rationale for precision targeting of PI3K{beta}-dependent cancers.

cancer biology↗