Biology subjects

Yao, R.

Publications and source records attributed to Yao, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Integrative analysis of the MDM2 promoter switch and cellular lineage plasticity in colorectal cancer: a contrast between the autonomous-proliferation type (CIN/CMS2) and the environment-adaptive type (MSI/gastric metaplasia)

Background: Biomarkers that stratify colorectal cancer (CRC) by therapeutic responsiveness and are measurable directly in biopsy specimens remain insufficiently established. We investigated whether usage of the dual MDM2 promoters (P1/P2) acts as a molecular switch separating two diametrically opposed CRC phenotypes: a chromosomal instability type and an environment adaptive type (microsatellite instability/serrated pathway with gastric metaplasia). Methods: Sixty three organoid samples from 22 patients with CRC were classified morphologically by deep learning (VGG16) and molecularly by an MDM2 Splicing Index derived from expression arrays. The P1 and P2 signatures (gene sets characterizing P1 and P2dominant samples) were externally validated in TCGA-COAD/READ (n = 624) and GSE39582 (n = 536), 1,160 cases in total, and therapeutic implications were tested in public cell line panels (GDSC2, DepMap) and in 65 lines of an independent patient derived CRC organoid biobank. Results: Deep learning morphological classification reached 98.5% test accuracy (64/65), and morphology corresponded to P1/P2 isoform usage: Type1 (compact glandular) morphology predominated in P1 dominant samples (median Type1 fraction 0.826 versus 0.444) and non Type1 (cystic mucinous) morphology in P2 dominant samples (AUC 0.79). Both signatures differed across the four consensus molecular subtypes , and the P2 signature was higher in mismatch repair deficient (microsatellite-unstable) tumors. Promoter usage quantified directly (P2_index) was higher in TP53 wild type tumors , consistent with P2 being p53-inducible. TP53 wild type cell lines were more sensitive to the MDM2 inhibitor Nutlin 3a and were more dependent on MDM2 in the DepMap CRISPR screen ; among 198 GDSC2 drugs, Nutlin 3a correlated most strongly with the P2 score. In the independent biobank, TP53 wild type lines (17) were more sensitive to nutlin-3 than mutant lines (48) (median log(IC50) 1.386 versus 4.283). Conclusions: MDM2 promoter choice (P1/P2) co-varies with the lineage identity of cancer cells and with the secretory, mucin rich character of the tumor tissue, consistent with a molecular-switch role alongside p53 suppression. The MDM2 P1/P2 ratio, measurable by RT qPCR or targeted NGS, is a candidate molecular-classification and therapeutic-stratification biomarker corresponding robustly to CMS, MSI, and TP53 mutation status.

bioinformatics↗

bioRxiv2026

Whole-body Super-resolution Functional and Molecular Imaging with Panoramic Photoacoustic-Ultrasound Tomography

Photoacoustic (PA) and ultrasound (US) imaging provide complementary molecular, functional, and anatomical contrasts. Here, we present a panoramic PA-US imaging platform that integrates multispectral PA computed tomography (PACT) along with reflection-mode and transmission-mode US imaging through a single shared full-ring ultrasound array. We employ an ultrafast planewave transmission scheme in reflection-mode US for power Doppler (PWD) imaging and ultrasound localization microscopy (ULM). Additionally, we use the transmission-mode US to reconstruct a spatially resolved speed of sound (SoS) map that corrects both PA and US reconstruction. Such correction sharpens the resolution of PACT, suppresses the artifacts of PWD, and improves microbubble localization of ULM. Elevational scanning further enables whole-body volumetric imaging with co-registered PA and US contrasts. The integrated system maps photoswitchable DrBphP1-expressing tumors alongside their blood perfusion and oxygenation environment. Applying the platform to monitor unilateral renal ischemia-reperfusion injury, we report that microvascular perfusion and renal oxygenation recover at different rates. Collectively, we demonstrate that the integrated PA-US imaging platform provides a unified framework for multiparametric study of anatomy, perfusion, microvascular flow, oxygenation, and molecular activities.

bioengineering↗

bioRxiv2026

LAND: Latent Aligned Neural-Behavioral Dynamics via Flow Matching forGeneralizable Movement Decoding

Generalizable movement decoding remains a central challenge for invasive brain--computer interfaces (BCIs), as decoders trained under limited calibration conditions often fail to generalize to unseen movement speeds, limbs, and subjects. Existing decoding methods are typically trained on paired data collected under restricted conditions. How to incorporate behavioral structure from unpaired data for robust out-of-distribution (OOD) decoding therefore remains unresolved. To address this, we propose LAND (Latent Aligned Neural-behavioral Dynamics), a framework that aligns latent neural and behavioral dynamics through flow matching. By learning a neural-to-behavioral transport map and using behavioral-dynamics priors from unpaired data to encourage structured neural manifolds, LAND regularizes representation geometry to promote cross-domain generalization. We evaluate LAND on synthetic neural data, epidural BCI recordings from a tetraplegia participant, and multi-electrode array (MEA) recordings from nonhuman primates (NHPs). Across these settings, LAND improves zero-shot generalization to OOD movement speeds and yields speed-modulated manifolds. With limited target-domain fine-tuning, it further improves transfer across limbs and subjects. These results support flow-based neural--behavioral alignment with unpaired kinematic priors as an approach for learning transferable neural representations and robust movement decoding across behavioral and recording domains.

neuroscience↗

bioRxiv2026

3D Passive Cavitation Mapping (3D-PCM) with a Large-aperture Planar Array

Urinary stone disease is a common urological condition with increasing incidence, particularly in developed countries. Laser lithotripsy (LL) has become a preferred minimally invasive treatment due to its high precision and low tissue damage. Recent studies suggest that cavitation plays a critical role in stone damage during LL, and three-dimensional passive cavitation mapping (3D-PCM) has emerged as a promising tool for detecting these events. However, clinical translation of 3D-PCM remains challenging due to limitations in imaging depth, field of view (FOV), and procedural compatibility. Here, we present a large-FOV dual-modality imaging system (3D-PCM and B-mode ultrasound) based on a large-aperture planar ultrasound array. Through array optimization and model-based reconstruction, our system achieves an expanded FOV of [~]40 x 40 mm2 at a clinically relevant imaging depth of [~]110 mm, while maintaining high spatial resolution of [~]0.6 mm laterally and [~]0.4 mm axially. In vivo experiments in a porcine model demonstrate that the reconstructed cavitation distribution correlates well with stone damage. Our technology has the potential to provide real-time treatment feedback during LL without disrupting the standard workflow.

bioengineering↗

bioRxiv2026

Prostaglandin E2 facilitates reciprocal crosstalk between intestinal smooth muscle tissue and epithelium in tumor development

Colorectal cancer arises from intestinal epithelial cells and is driven by the accumulation of aberrant signaling events that disrupt intestinal stem cell (ISC) homeostasis. While stromal regulation of the ISC niche is increasingly recognized, the contribution of the underlying/adjacent smooth muscle tissue (SMT) remains poorly characterized. In particular, the potential crosstalk between normal or tumoral epithelium and the SMT is largely unexplored. Here, we investigate the ability of the SMT in modulating normal and tumorigenic epithelial biology, and the impact of the tumoral epithelium on the underlying SMT. Mechanistically, by using imaging analyses, transcriptomics, and mass spectrometry, we identify the SMT-derived factor Prostaglandin E2 (PGE2) as the key driver of epithelial dedifferentiation, promoting YAP transcriptional activation, organoid enlargement, and spheroid morphology in intestinal epithelial organoids following SMT supernatant exposure. Conversely, we show that non-invasive tumoral epithelium induces significant changes in the underlying SMT. Tumor-associated SMT shows structural remodeling, inflammation, and reduced muscle fitness. Furthermore, we detected increased prostaglandin signaling, including upregulation of PGE2 synthase Ptgs1 (COX1), in the SMT underneath the epithelial tumor. Our results reveal a communication between the tumoral epithelium and the underlying SMT prior to metastasis, which could be a facilitating step for tumoral extramural progression. Taken together, these findings highlight a novel tumor-stroma interaction.

Molecular Biology↗

bioRxiv2026

Three-Dimensional Photoacoustic Tomography with Ultrasound Localization Priors

Three-dimensional photoacoustic tomography (3D-PAT) enables noninvasive structural and functional imaging with optical absorption contrast and ultrasonic detection depth. However, its spatial resolution is limited by acoustic diffraction, and incomplete detection geometry can substantially degrade image fidelity and quantitative accuracy. Here, we present a ULM-guided model-based reconstruction framework, termed 3D-PAULMprior that incorporates sub-diffraction vascular priors from concurrent ultrasound localization microscopy (ULM) into 3D photoacoustic reconstruction. The method uses weighted regional Laplacian regularization to integrate high-resolution vascular information into the inverse problem, thereby enhancing vascular sharpness, suppressing limited-view artifacts, and improving blood oxygen saturation estimation. We validated 3D-PAULMprior using numerical simulations, tissue-mimicking phantoms, and in vivo mouse brain imaging. Compared with conventional reconstruction, 3D- PAULMprior improved spatial resolution by over 50%, increased contrast-to-noise ratio by 261.2%, and enhanced structural similarity index by 24.6%. In vivo, 3D-PAULMprior recovered vascular structures that were poorly resolved or missing in conventional reconstructions and produced more spatially confined sO2 maps. These results establish 3D-PAULMprior as a robust multimodal reconstruction strategy for high-resolution structural and functional photoacoustic imaging.

bioengineering↗

bioRxiv2026

3D-PAULM: Integrated Photoacoustic Tomography and Ultrasound Localization Microscopy for Multiparametric Brain and Tumor Imaging

Understanding processes such as blood-brain barrier (BBB) disruption and tumor progression can greatly benefit from simultaneous molecular, functional, and hemodynamic imaging in deep tissue, yet few existing imaging modalities can provide all three in a single system. Here, we present an integrated imaging platform that combines 3D photoacoustic tomography with ultrasound localization microscopy (3D-PAULM) to enable intrinsically co-registered, multiparametric imaging. 3D-PAULM unifies multispectral photoacoustic molecular imaging, ultrasound B-mode imaging, microbubble-enhanced power Doppler, and ultrasound localization microscopy, and concurrently measures blood oxygenation, blood perfusion, microvascular flow dynamics, and molecular probes from near-infrared dyes and photoswitchable phytochromes. We apply 3D-PAULM to quantify BBB leakage in focal ischemia and systemic inflammation, and to perform high-sensitivity molecular imaging of solid tumors alongside functional mapping of tumor hypoxia and super-resolved vascular remodeling. Together, these results establish 3D-PAULM as a versatile platform for integrated functional and molecular imaging in deep tissue.

bioengineering↗

bioRxiv2026

Photoacoustic Fingerprinting for Robust Molecular Imaging

Quantitative molecular imaging in photoacoustics is fundamentally limited by the ill-posed nature of spectral unmixing, where spectral overlap, noise, and unknown fluence introduce bias in conventional inversion-based methods. We introduce photoacoustic fingerprinting (PAF), a framework that reframes spectral unmixing as a fingerprint recognition problem. PAF interprets multispectral signals as high-dimensional fingerprints encoding both molecular composition and measurement distortions. Inspired by magnetic resonance fingerprinting, PAF uses a recurrent neural network trained on synthetic data spanning realistic mixtures, noise levels, and fluence variations to directly infer molecular concentrations from spectral shape. PAF enables accurate and robust quantification in regimes where conventional methods break down, including low signal-to-noise conditions, spectrally correlated mixtures, and unknown fluence distortions. In controlled simulations, PAF consistently outperformed non-negative least squares, with the largest gains observed for spectrally overlapping chromophores such as collagen. In phantom studies, PAF improved molecular specificity by correctly localizing collagen and recovering water contrast despite similar spectral reconstructions. In ex vivo mouse livers, PAF detected lipid accumulation associated with steatosis, and in human arteries, it identified molecular signatures consistent with thrombus and lipid-rich plaque. These results establish PAF as a generalizable framework for label-free molecular imaging and a promising step toward quantitative photoacoustic diagnostics.

biochemistry↗

bioRxiv2026

Metabolic Engineering Boosts Strigolactone Production in Nicotiana benthamiana and Uncovers a Novel P450 Function

Strigolactones (SLs) are plant hormones regulating shoot branching and symbiotic interactions, but their trace-level abundance limits research and applications. Here, we optimized a Nicotiana benthamiana transient expression system for SL production by tuning agroinfiltration parameters and co-expressing rate-limiting carotenoid biosynthetic genes. Overexpression of Zea mays PSY1 or an Arabidopsis PSY-GGPS11 fusion increased carlactone production over 2-fold and enhanced downstream SL accumulation. Using this platform, we discovered that sorghum cytochrome P450 SbCYP728B35 catalyzes conversion of 5-deoxystrigol to sorgolactone, revealing a previously unknown function. These results establish metabolic engineering of precursor supply as an effective strategy for boosting SL production and demonstrate N. benthamiana as a robust system for pathway elucidation and biotechnological synthesis of bioactive strigolactones.

plant biology↗

bioRxiv2026

Biomimetic model for the identification of distinctive microenvironmental factors in glioblastoma radiosensitivity

Radiation therapy (RT) has long been included in the treatment of glioblastoma (GBM). However, radioresistance in cancer cells as well as toxicity in normal tissues are major obstacles to clinical efficacy. Improved understanding of the mechanisms of tumor microenvironment-induced radioresistance during and after radiation therapy can provide fundamental insights to improve clinical outcomes in GBM. Here, using three-dimensional engineered hydrogel models in vitro, we report the influence of extracellular matrix, hypoxia, and adjacent neuronal cells in radiotherapeutic sensitivity. We find that mechanical cues and oxygen availability regulate cellular response to radiation, with softer matrices allowing for more DNA damage. Hyaluronan fragments from the extracellular matrix also modulate rapid metabolic response to radiation, especially in hypoxic environments. We show that neuronal networks influence tumor metabolic activity and the inflammatory response. Overall, we demonstrate here that alternative radiation strategies, such as low dose rate radiation therapy and microenvironmental regulation, have the potential to be more effective in a specific subset of radiosensitive GBM tumors.

bioengineering↗

bioRxiv2025

APETALA2 controls seed growth by regulating outer integument mechanical identity during seed coat differentiation

Organ morphogenesis requires differentiating cells to acquire mechanical properties that precisely regulate growth. In Arabidopsis thaliana, seed size and shape are largely controlled by the outer integument of the seed coat, whose two layers develop distinct mechanical behaviors critical for growth regulation. Here, we show that the cell identity factor APETALA2 (AP2) both promotes and restricts seed growth by coordinating the post-fertilization differentiation of these layers into distinct seed coat tissues. AP2 drives layer-specific remodeling of cell wall composition, notably affecting pectin and xyloglucan, thereby establishing contrasting mechanical properties between the two layers. Unexpectedly, these changes in wall composition and mechanics do not alter mechanosensitive responses, revealing a surprising uncoupling between cell wall remodeling and mechanotransduction. Our findings identify AP2 as a key coordinator of tissue-specific mechanical differentiation during organ morphogenesis.

plant biology↗

bioRxiv2025

Elevated Temperatures Representing Heatwave Conditions Shift Active Nitrifying Communities and Their Viruses in Tidal Flats and Agricultural Soils

Global heatwave intensification associated with climate change will impact the nitrogen cycle, yet its effect on specific nitrifier groups or their interactions with viruses remains unclear. Using 13CO2-DNA-based stable isotope probing (SIP) coupled with metagenomics, we show that elevated temperatures associated with heatwave conditions restructure active nitrifying communities and their viruses in Yangtze River estuary tidal flats and adjacent agricultural soils. In tidal flats, high temperatures shifted active ammonia-oxidizing archaea and bacteria (AOA and AOB), and nitrite-oxidizing bacteria (NOB) from marine to terrestrial ecotypes. In contrast, heatwave conditions stimulated terrestrial ecotypes of AOA but suppressed AOB in agricultural soils. 13C-labeled nitrifier-infecting viruses also showed temperature-driven shifts in activity, lifestyle, and auxiliary metabolic genes in concert with hosts. Notably, AOA viruses carried the plastocyanin gene, potentially augmenting host metabolism. These findings demonstrate heatwaves drive complex shifts in nitrifier communities and their interactions with viruses, impacting global nutrient cycling under climate extremes.

microbiology↗

bioRxiv2025

Quantitative Prevalence, Chemical Speciation, and ECM-Embedded Networks of Biogenic Silicon in Animal Tissues Revealed by Refined Analytical Methods

Silicon, abundant in Earths biosphere, plays crucial roles in many organisms. However, its biological functions in animals remain inadequately characterized, primarily constrained by methodological limitations in quantifying, identifying, and visualizing biogenic silicon in tissues. Here, we refined the molybdenum blue colorimetric method (MB) for more accurate silicon quantification, developed integrated mass spectrometry techniques to delineate chemical natures of biogenic silicon, and optimized micro-X-ray fluorescence (micro-XRF) imaging for spatial mapping in animals. Employing these methodologies, we demonstrated that silicon abundance in animals substantially exceeds prior estimates--surpassing essential elements like iron. We also revealed the chemical architectures of diverse silicon compounds and visualized tissue-specific distributions in mice and humans, indicating its predominant localization within extracellular matrix (ECM) and suggesting the formation of silicified networks. These findings establish silicon as a structurally and quantitatively significant element with profound biological implications, warranting its recognition as an essential factor in human physiology and pathology.

biochemistry↗

bioRxiv2025

Transfer RNA modifications during rhizome development in Oryza longistaminata

The rhizome organ endows many clonal plants with the ability to reproduce under stressful climates. Such rhizome-mediated perenniality also underlies the recent success of perennial rice breeding. Despite the importance of this organ, its developmental regulation is poorly understood. Here, using Oryza longistaminata, an emerging model for rhizome biology, we explored the involvement of tRNA modification in rhizome development. Through comparative profiling of modified nucleotides in rhizome samples at different developmental stages and/or subjected to various treatments, we identified a number of key rhizome-related tRNA modifications and revealed that, akin to the observations in many non-plant organisms, tRNA modifications are associated with hormonal signalling to regulate rhizomes responses to environmental cues. Furthermore, genome-wide analysis of tRNA-modifying genes was performed to facilitate future functional studies. These results and analyses not only deepen our understanding of rhizome development but also underscore the regulatory roles of tRNA modification in plant organ development.

plant biology↗

bioRxiv2025

Beyond the Anterior Temporal Lobe: Domain-Related Degeneration of Cortical Language Network Dynamics in Semantic Dementia

Semantic dementia (SD) is a neurodegenerative disorder marked by a progressive decline in semantic memory, mainly due to focal atrophy in the anterior temporal lobe (ATL). As the disease advances, atrophy spreads to the perisylvian regions, accompanied by non-semantic language impairments. Despite these clinical findings, the network mechanisms behind cross-domain linguistic deficits remain poorly understood. In this study, we used our recently developed meta-networking framework of cortical language network dynamics to systematically examine domain-specific network disruptions in SD. Using resting-state functional MRI (fMRI) and comprehensive neuropsychological tests across several language domains, we analyzed data from SD patients at two timepoints: baseline (n = 42) and a 2-year follow-up (n = 24). Our findings showed that the framework successfully identified domain-specific language network degeneration. Beyond the ATL, progressive atrophy disrupted the dynamic separation of language networks involved in semantic processing, phonological processing, and speech production. These disruptions were characterized by state-specific hypo- and hyper-connectivity patterns that related to distinct language impairments. At follow-up, atrophy extended to posterior temporal and prefrontal regions, worsening network function. Importantly, the patterns of language network disruption predicted individual language deficits, providing a mechanistic link between structural degeneration, functional network changes, and clinical symptoms.

neuroscience↗

bioRxiv2025

Multi-scale structure of chromatin condensates rationalizes phase separation and material properties

Biomolecular condensates, compartments that concentrate molecules without surrounding membranes, are integral to numerous cellular processes. The structure and interaction networks of molecules within condensates remain poorly understood. Using cryo-electron tomography and molecular dynamics simulations we elucidated the structure of phase separated chromatin condensates across scales, from individual amino acids to network architecture. We found that internucleosomal DNA linker length controls nucleosome arrangement and histone tail interactions, shaping the structure of individual chromatin molecules both within and outside condensates. This structural modulation determines the balance between intra- and intermolecular interactions, which in turn governs the molecular network, thermodynamic stability, and material properties of chromatin condensates. Mammalian nuclei contain dense clusters of nucleosomes whose non-random organization is mirrored by the reconstituted condensates. Our work explains how the structure of individual chromatin molecules ultimately determines physical properties of chromatin condensates, with implications for cellular chromatin organization.

biophysics↗

bioRxiv2024

Memorize multiple phase pattern attractors in nonlinear coupled oscillators dynamic via heterogeneous connectivity strength

Whole brain neural oscillation activities exhibit multiple wave patterns and seem to be supported by the common circuit network structure. We proposed a Hebbian-like Kuramoto model based entirely on heterogeneous connectivity strength rather than phase delay, which encodes the multiple phase patterns as attractors. We systematically investigated how the model dynamic landscape influenced by attractors and their corresponding eigenvalues, as well as how to control the stability of equilibrium points and the occurrence of high dimension bifurcations. This framework enables us to reproduce the dominant wave activity components in human brain functional MRI signal, and provides a canonical model for the multi body physical system spatio-temporal pattern attractor dynamics.

neuroscience↗

bioRxiv2024

Decoding cell identity with multi-scale explainable deep learning

Cells are the fundamental structural and functional units of life. Studying the definition and composition of different cell types can help us understand the complex mechanisms underlying biological diversity and functionality. The increasing volume of extensive single-cell omics data makes it possible to provide detailed characterisations of cell types. Recently, there has been a rise in deep learning-based approaches that generate cell type labels solely through mapping query data to reference data. However, these approaches lack multi-scale descriptions and interpretations of identified cell types. Here, we propose Cell Decoder, a biological prior knowledge informed model to achieve multi-scale representation of cells. We implemented automated machine learning and post-hoc analysis techniques to decode cell identity. We have shown that Cell Decoder compares favourably to existing methods, offering multi-view interpretability for decoding cell identity and data integration. Furthermore, we have showcased its applicability in uncovering novel cell types and states in both human bone and mouse embryonic contexts, thereby revealing the multi-scale heterogeneity inherent in cell identities.

bioinformatics↗