Biology subjects

Yu, G.

Publications and source records attributed to Yu, G..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Time-Resolved Laser Speckle Contrast Imaging (TR-LSCI) of Cerebral Blood Flow Response to Intracranial Pressure Elevation

SignificanceCerebral autoregulation (CA) reflects the dynamic coupling among cerebral blood flow (CBF), intracranial pressure (ICP), and arterial blood pressure (ABP); its failure contributes to secondary brain injury. Existing bedside methods rely on indirect or spatially limited CBF surrogates and cannot resolve microvascular flow dynamics across space, depth, and time. AimTo develop, optimize, and apply a scalable, noncontact time-resolved laser speckle contrast imaging (TR-LSCI) platform for depth-sensitive, high-speed, wide-field CBF imaging during controlled ICP perturbations. ApproachTR-LSCI synchronizes a 20-MHz pulsed laser with a time-gated, single-photon avalanche diode (SPAD) camera (512 x 512 pixels) to detect diffuse photons at varying path lengths, enabling depth-resolved microvascular CBF imaging. Benchtop and mobile TR-LSCI systems were applied in adult rats and a neonatal piglet with synchronized invasive ICP and ABP measurements. ResultsTR-LSCI captured spatially heterogeneous, pulsatile CBF dynamics at up to 52 Hz over large cortical fields of view, with heart rate estimates statistically equivalent to those from ICP and ABP. Multivariable analysis identified reproducible, phase-dependent CA transitions encompassing preserved autoregulation, ABP-driven compensation, and ICP-constrained CBF suppression; notably, CBF alone exhibited distinct phase signatures. ConclusionsTR-LSCI enables dynamic, physiology-informed neurovascular monitoring and supports future bedside CA assessment.

neuroscience↗

bioRxiv2026

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↗

bioRxiv2026

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↗

bioRxiv2026

Astrocyte-induced internal state transitions reshape brainwide sensory, integrative, and motor computations

Animals rapidly adapt to changing circumstances by shifting how they perceive, integrate, and act. Such flexibility is often attributed to transitions between internal states that exert widespread influence across the brain. Yet the mechanisms that drive state transitions and how they reconfigure brainwide computation remain unclear. Larval zebrafish, when actions are rendered futile by decoupling visual flow feedback from swimming in virtual reality, enter a temporary passive, energy-preserving state. In this state, astrocyte calcium levels are elevated, and swim reinitiation requires greater accumulated visual motion. Using whole-brain, cellular-resolution activity imaging, we observed widespread circuit alterations underlying this disengaged state: neuronal visual responses weakened, visual motion integration over time became dramatically leakier, motor inhibition increased, and motor preparation slowed, together suppressing conversion of sensory evidence into action. Astrocyte calcium rose during futile swimming, tracked the emergence and resolution of these brainwide changes, and was both necessary and sufficient to drive them. Thus, astrocytes orchestrate internal states that profoundly reshape neural computations, most powerfully at intermediate integrative processing stages, to meet changing demands. HighlightsO_LIInternal state change alters brainwide neuronal processing at every stage of the sensorimotor transformation C_LIO_LIEffects are most powerful at integrative stages through stimulus memory collapse C_LIO_LIAs state resolves, amplification of sensory representations synergizes with reduced motor inhibition for action reinitiation C_LIO_LIAstrocyte activity drives these brainwide adaptive shifts in neuronal dynamics C_LI

neuroscience↗

bioRxiv2026

ARUNA: Slice-based self-supervised imputation for upscaling DNA methylation sequencing assays

Whole-genome bisulfite sequencing (WGBS) can provide near-comprehensive, base-resolution maps of DNA methylation, transforming our understanding of epigenetic regulation in development and disease, but its cost is often prohibitive for many studies. Reduced representation bisulfite sequencing (RRBS) offers a cost-effective alternative that profiles a CpG-enriched subset of the genome at base resolution. Similar sequencing protocols for both assays pose an opportunity for cross-assay integration, presenting an opportunity for massively increasing sample sizes at whole-genome resolution. However, existing imputation methods are designed for within-assay scenarios and cannot handle the substantial CpG coverage differences between WGBS and RRBS. We introduce ARUNA, a self-supervised denoising convolutional autoencoder that predicts genome-wide CpG-level methylation using only a small subset of observed methylation values and CpG coordinates. By modeling methylation "slices," spatially stacked windows that preserve local correlation structure, ARUNA captures biologically meaningful covariation while avoiding representation collapse. In simulation studies using the GTEx dataset, ARUNA successfully upscales RRBS-scale sparse methylomes (80-95% missingness) to whole-genome resolution, consistently outperforming baselines and maintaining robust performance across donor and tissue holdouts. When applied to real RRBS data from the ENCODE dataset, ARUNA outperformed state-of-the-art methods, with performance validated by matching upscaled RRBS samples to isogenic WGBS replicates. Source code for ARUNA can be found at https://github.com/ylaboratory/ARUNA.

bioinformatics↗

bioRxiv2026

Interferon Beta Drives Therapy Resistance in a Patient Derived Model of High Grade Serous Ovarian Cancer

Cancer cell-autonomous type 1 interferon (IFN-1) production and signaling is frequently activated in response to DNA damage and has been associated with the development of therapy resistance in several cancer types. However, its cell-autonomous role in driving resistance in high-grade serous ovarian cancer (HGSOC), a disease defined by near-universal exposure to genotoxic therapy as frontline treatment, remains unclear. Specifically, whether IFN-1 functions in HGSOC as only a response to genotoxic stress or can independently act in driving resistance phenotypes has not been studied. Utilizing a syngeneic patient-derived model of cisplatin-sensitive (SE) and -resistant (CR) HGSOC, we demonstrate that chronic cisplatin exposure is associated with enrichment of IFN-1 signaling and the interferon-related DNA damage resistance signature (IRDS). Acute cisplatin treatment elicited dynamic, temporal IFN-1 signaling and responses in both sensitive and resistant cells, indicating a conserved stress response in resistant cells. Chronic, low-level exposure to exogenous IFN{beta}, in the absence of a DNA-damaging agent, was sufficient to phenocopy several features of chronic cisplatin driven resistance, including reduced therapeutic sensitivity, cell cycle arrest, and decreased proliferation. Notably, IFN{beta} driven resistance occurred without sustained IRDS or canonical interferon stimulated gene (ISG) induction, revealing alternative mechanisms for IFN-1 mediated therapy resistance. Together, these findings identify IFN{beta} as a functional driver of the development of resistance-associated phenotypes and highlight cell-autonomous IFN-1 signaling as a potential biomarker for resistance and a therapeutic target in platinum-resistant disease.

cancer biology↗

bioRxiv2026

Modeling predicts a biochemical feedback mechanism underlying astrocyte calcium refractory periods

Astrocytes exhibit intracellular calcium fluctuations in response to neuronal activity. Repeated receptor stimulation can induce a transient suppression of calcium signaling--a refractory period--yet the underlying mechanisms and timescales of this phenomenon during behavior remain poorly understood. Here, we present a biophysically grounded computational model of astrocytic calcium signaling that incorporates a novel feedback mechanism mediated by conventional protein kinase C (cPKC) and predicts the refractory phenomenon. Unlike previous models developed in vitro, our model is directly validated using in vivo two-photon calcium imaging data from behaving mice. It closely recapitulates astrocytic calcium dynamics across both time and frequency domains, including the emergence of refractory periods and their negative correlation with inter-stimulus intervals. Simulations further predict the timing of recovery from refractory states, consistent with experimental observations. This work provides a mechanistic explanation for astrocytic refractory behavior and establishes a framework for integrating computational modeling with in vivo functional imaging.

neuroscience↗

bioRxiv2026

Engineering Functionality-Optimized Fully Human B7-H3 CAR T Cells for Enhanced Solid Tumor Therapy

B7-H3 is a cell surface protein overexpressed in many solid tumors and an attractive target for chimeric antigen receptor (CAR) T cell therapy. The most clinically advanced B7-H3 CARs are derived from murine monoclonal antibodies (mAbs) 376.96 and MGA271, which are now in phase 1/11 trials. However, non-human mAb sequences can provoke immune responses, leading to CAR T-cell rejection and therapeutic failure. Although scFv humanization reduces this risk, residual foreign residues within the variable domains remain. To overcome this limitation, we used in vitro phage display to generate fully human B7-H3-specific scFvs for CAR design. In pancreatic cancer, neuroblastoma, and glioblastoma xenograft models, CAR T cells incorporating the lead human binder Y111 were well tolerated and demonstrated superior antitumor activity compared with 376.96- and MGA271-based CARs. Y111 CAR treatment induced complete responses, tumor rejection, and significant survival benefits, identifying Y111 as a promising fully human B7-H3 CAR for solid tumors.

immunology↗

bioRxiv2026

AN OPTIMIZED METHOD TO DIFFERENTIATE HL60 CELLS INTO NEUTROPHIL-LIKE CELLS

The HL60 promyelocytic leukemia cell line is widely used to investigate neutrophil biology due to its genetic tractability and accessibility. HL60 cells can be differentiated into neutrophil-like cells using all-trans retinoic acid (ATRA) or dimethyl sulfoxide (DMSO) treatment. However, these approaches produce cells that lack critical features of mature granulocytes, such as robust chemotaxis with ATRA treatment or multilobed nuclear morphology with DMSO treatment. To overcome these limitations, we developed a sequential differentiation protocol - ATRA for one day followed by DMSO for four days (A1D4) - which yields neutrophil-like cells that more faithfully recapitulate the morphology and functionality of mature human neutrophils. A1D4-differentiated HL60 cells display segmented nuclei with low lamin A/C expression and demonstrate strong chemotactic, oxidative burst, and phagocytic activity. This protocol combines the advantages of individual compounds, producing cells that closely mimic primary neutrophils in both phenotype and function. SUMMARY SENTENCEThe authors provide an improved method to differentiate HL60 cells into neutrophil-like cells that faithfully recapitulates the morphology and functionality of mature human neutrophils.

immunology↗

bioRxiv2026

Disrupted dynamics of brain structure function coupling link genetic risk of Alzheimer's Disease and aging to cognitive decline in 34,067 adults

AbstractUnderstanding how a stable structural connectome supports flexible cognition, especially in aging, is a fundamental question in neuroscience. While static structure-function coupling (SFC) is well-studied, the dynamic decoupling of functional activity from structural constraints--dynamic SFC (DSFC)--remains poorly understood. Leveraging MRI data from 34,067 UK Biobank participants (ages 45-82), we characterized the distinct roles of SFC and DSFC in aging, cognition, and health. We found that SFC and DSFC followed spatially divergent aging trajectories: SFC declined primarily in sensorimotor systems, whereas DSFC decreased most prominently in higher-order networks. Both SFC and DSFC in higher-order networks were positively correlated with cognitive performance (e.g., fluid intelligence). However, the associations with mental and physical health diverged between the two measures: reduced DSFC was predominantly linked to health burdens in high-order default/limbic networks, whereas weakened SFC was primarily associated with health burdens in low-order sensory-motor networks. Genetic analyses revealed that Alzheimers risk, specifically APOE {varepsilon}4 dosage, significantly reduced DSFC in higher-order cognitive networks and SFC in visual cortex. Mediation analyses further demonstrated that aging and APOE {varepsilon}4-linked cognitive decline were mediated via visual SFC and ventral attention DSFC. These findings position static and dynamic coupling as complementary mechanisms: static SFC preserves network robustness, while dynamic SFC enables transient reconfiguration for complex integration. Together, our results highlight these dual mechanisms as crucial for maintaining cognitive flexibility, providing potential biomarkers for age-related neurodegeneration.

neuroscience↗

bioRxiv2025

The CCCH Zinc Finger Gene PgCCCH50 from Pearl Millet Confers Drought and Salt Tolerance through an ABA-Dependent PgAREB1-PgCCCH50 Module

Abiotic stresses like drought and salinity severely constrain crop productivity. Pearl millet (Pennisetum glaucum L.), a stress-resilient cereal of global importance, is ideal for deciphering genetic adaptation. Although CCCH zinc finger proteins play key roles in plant stress responses, members with multiple regulatory functions remain unknown in this crop. This study analyzed 53 CCCH genes in pearl millet, examining their phylogeny, structure, chromosomal localization, and promoter cis-elements. Expression profiling revealed seven CCCH genes responsive to multiple stresses. Functional characterization of PgC3H50 showed that its overexpression in Arabidopsis conferred enhanced tolerance to drought and salt, evidenced by improved physiological parameters and upregulation of stress-responsive genes. We discovered that the ABA-responsive transcription factor PgAREB1(ABSCISIC ACID RESPONSIVE ELEMENT BINDING PROTEIN 1) directly binds to ABRE cis-elements in the PgC3H50 promoter and activates its transcription, validated by yeast one-hybrid, dual-luciferase, and EMSA assays. This defines a novel PgAREB1-PgC3H50 regulatory module within the ABA-mediated stress signaling pathway. Our findings provide a valuable genetic resource for the pearl millet CCCH family and unveil a promising candidate gene and transcriptional regulatory module for engineering crops with improved tolerance to drought and salinity. HighlightThis study reports the first genome-wide analysis of the CCCH family in pearl millet and identifies the novel PgAREB1-PgCCCH50 module as essential for salt and drought tolerance.

plant biology↗

bioRxiv2025

Beyond Cell Cycle Control: CDKN2A Loss Orchestrates NAD⁺ Metabolic Plasticity and NAMPT Inhibitor Sensitivity in Glioblastoma

While CDKN2A loss is classically associated with cell cycle deregulation through the p16-Cdk4-Rb axis, our findings suggest an additional layer of metabolic vulnerability arising from altered NAD homeostasis in CDKN2A-deleted glioblastoma, revealing a previously unrecognized metabolic-genetic interface for rationally revisiting NAD+ targeting strategies, moving beyond the broad inhibition approaches.

cancer biology↗

bioRxiv2025

Mineral guided molecular enrichment: An interfacial driving force for protocell emergence on early Earth

The emergence of protocells from a dilute prebiotic environment is a fundamental challenge in origins-of-life research. which requires the simultaneous overcoming of molecular dilution, the establishment of metabolic cycles and the formation of selectively permeable compartments. But where and how such critical conditions are satisfied is very obscure and debated. We demonstrate, using contemporary model proteins and enzymatic systems, that mineral surfaces can facilitate the co-adsorption and spatial arrangement of nucleotides, proteins, and lipids into locally enriched, protocell-like assemblies under the examined laboratory conditions. We showed that geochemically relevant minerals efficiently co-adsorb and colocalize diverse biomolecules, creating crowded interfacial microenvironments that support enzyme cascades with substrate channeling-like behavior. Subsequently, these mineral-protein complexes template the assembly of lipid membranes, leading to the formation of discrete compartments that maintain metabolic activity while permitting molecular exchange. This mineral-guided surface enrichment (MSE) mechanism integrates key aspects of "metabolism-first" and "membrane-first" scenarios into a unified pathway, reconciling long-standing conceptual divides in prebiotic chemistry. Our findings establish mineral interfaces as active organizers of protocell emergence, offering a geochemically plausible framework for the origin of cellular life.

evolutionary biology↗

bioRxiv2025

USP-ddG: A Unified Structural Paradigm with Data Efficacy and Mixture-of-Experts for Predicting Mutational Effects on Protein-Protein Interactions

Accurately estimating changes in binding free energy ({Delta}{Delta}G) is essential for understanding protein-protein interactions (PPIs) and guiding rational protein design. Existing deep learning approaches benefit from pre-training on large structural datasets, but they often require heavy computation and overlook data efficacy. In addition, prior models typically assume fixed backbone structures and ignore conformational dynamics, limiting generalization. We present USP-ddG, a unified structural paradigm for{Delta}{Delta} G prediction. USP-ddG integrates a dual-channel architecture with three complementary components: (i) inverse folding-based log-odds ratio, (ii) empirical energy terms from FoldX, and (iii) a geometric encoder with Gaussian noise to capture relaxed conformations. To enhance representation power, we introduce a framework that integrates feed-forward network (FFN) and Mixture-of-Experts (MoE) to model domain-invariant and -specific features, respectively. We further propose CATH-guided Folding Ordering (CFO), a data efficacy strategy that organizes samples to mitigate catastrophic forgetting and data distribution bias. USP-ddG consistently outperforms existing state-of-the-art (SoTA) methods on the SKEMPI v2.0 benchmark, including the challenging hold-out CATH test set. It achieves superior accuracy on both single- and multi-point mutations and demonstrates strong performance in antibody affinity optimization against H1N1 and HER2, and in assessing SARS-CoV-2 variants to hACE2. Ablation studies confirm the benefit of each component. These results highlight USP-ddG as a robust and data-efficient framework for modeling mutational effects on PPIs. AvailabilityUSP-ddG is publicly available at https://github.com/ak422/USP-ddG.

molecular biology↗

bioRxiv2025

The emerging contaminant Cl-PFESA/F-53B is toxic to meiotic cell division and reproduction in Arabidopsis thaliana

The emerging contaminant Cl-PFESA/F-53B damages vegetative development in plants and has been evidenced to be toxic to both mitotic and meiotic cells in animals. We have recently reported that F-53B induces nuclei unviability in meristematic cells leading to disrupted root development in Arabidopsis (Arabidopsis thaliana). However, the toxicity of F-53B to reproductive system in plants remains unelucidated. In this study, by using cytogenetic and microscopic approaches, we analyzed embryo and anther development and multiple meiosis processes in Arabidopsis exposed to 50 or 100 M F-53B. We showed that F-53B disrupts embryo development which results in reduced seed setting in Arabidopsis. Histochemical staining of anthers and a live-imaging assay using a reporter line that expresses GFP-tagged Aborted Microspores (AMS), a key regulator of the tapetum, demonstrated that F-53B impairs anther development. Moreover, we showed that F-53B interferes with chromosome segregation and/or distribution and alters microtubule organization during male meiosis. Quantification of the chiasmata and immunolocalization of the Human Enhancer of Invasion 10 (HEI10) protein on diakinesis chromosomes suggested that F-53B reduces crossover rate. Furthermore, F-53B reduced the number of DNA Meiotic Recombinase 1 (DMC1) protein foci on zygotene chromosomes in Arabidopsis wild-type Columbia-0 (Col-0), and it partially promoted meiotic chromosome integrity in Arabidopsis depleted with Ataxia Telangiectasia Mutated (ATM), a central regulator of DNA double-strand break (DSB) repair, which suggested that F-53B reduces meiotic DSB formation. Taken together, our study reveals the toxicity of F-53B to meiotic cells and reproduction in Arabidopsis, which highlights its potential threats to agricultural safety and ecological diversity. HighlightO_LIF-53B impairs embryo and anther development in Arabidopsis. C_LIO_LIF-53B interferes with chromosome segregation and distribution during male meiosis. C_LIO_LIF-53B interferes with meiotic microtubule organization. C_LIO_LIF-53B reduces meiotic crossover formation. C_LIO_LIF-53B reduces DNA double-strand breaks in meiocytes. C_LI

plant biology↗

bioRxiv2025

Physics-Diffusion-Driven Multiscale Aggregation for Drug-Target Interaction Prediction

Drug-target interaction prediction is an important task in computational drug discovery. To address the limitations of existing graph neural network approaches in propagation depth and robustness, we propose PDDMA-DTI (Physics-Diffusion-Driven Multiscale Aggregation for Drug-Target Interaction Prediction), a physics-inspired, multiscale adaptive aggregation framework. PDDMA-DTI injects a physics-motivated diffusion operator into a heterogeneous drug-target network: global diffusion models cross-modal information propagation via the graph Laplacian, while local diffusion performs neighborhood smoothing in the low-dimensional embedding space. Both processes are solved with the implicit Euler scheme to ensure numerical stability. For each node, we introduce an adaptive stopping rule based on steady-state convergence and a weighted fusion strategy. This strategy leverages hop counts and node degrees to aggregate multi-step diffusion snapshots into a final representation that preserves original features while capturing multi-scale context. To emphasize strong interaction pathways, we further propose a Physical Interaction Summation Enhancement module that augments pairwise interaction features with a linear plus quadratic energy term, thereby amplifying highly correlated drug-target pairs. Extensive experiments on multiple benchmark datasets show that PDDMA-DTI consistently outperforms representative baselines in accuracy and robustness.

bioinformatics↗

bioRxiv2025

Imaging cellular activity simultaneously across all organs of a vertebrate reveals body-wide circuits

All cells in an animal collectively ensure, moment-to-moment, the survival of the whole organism in the face of environmental stressors1,2. Physiology seeks to elucidate the intricate network of interactions that sustain life, which often span multiple organs, cell types, and timescales, but a major challenge lies in the inability to simultaneously record time-varying cellular activity throughout the entire body. We developed WHOLISTIC (WHole Organism Live Imaging System for recording Tissue and IntraCellular activity), a method to image second-timescale, time-varying intracellular dynamics across cell-types of the vertebrate body. By advancing and integrating volumetric fluorescence microscopy, machine learning, and pancellular transgenic expression of calcium sensors in transparent young Danio rerio (zebrafish) and with proof of concept in adult Danionella, the method enables real-time recording of cellular dynamics across the organism. Calcium is a universal intracellular messenger, with a large array of cellular processes depending on changes in calcium concentration across varying time-scales, making it an ideal proxy of cellular activity3. Using this platform to screen the dynamics of most cells in the body, we discovered unexpected responses of specific cell types to stimuli, such as chondrocyte reactions to cold, meningeal responses to ketamine, and state-dependent activity, such as oscillatory ependymal-cell activity during periods of extended motor quiescence. At the organ scale, the method uncovered pulsating traveling waves along the kidney nephron. At the multi-organ scale, we uncovered muscle synergies and independencies, as well as muscle-organ interactions. Integration with optogenetics allowed us to all-optically determine the causal direction of brain-body interactions. At the whole-organism scale, the method captured the rapid brainstem-controlled redistribution of blood flow across the body. Finally, we advanced Whole-Body Expansion Microscopy4 to provide ground-truth molecular and ultrastructural anatomical context, explaining the spatiotemporal structure of activity captured by WHOLISTIC. Together, these innovations establish a new paradigm for systems biology, bridging cellular and organismal physiology, with broad implications for both fundamental research and drug discovery.

neuroscience↗

bioRxiv2025

DANCE 2.0: Transforming single-cell analysis from black box to transparent workflow

Preprocessing is a critical step in single-cell data analysis, yet current practices remain largely a black-box, trial-and-error process driven by user intuition, legacy defaults, and ad hoc heuristics. The optimal combination of steps such as normalization, gene selection, and dimensionality reduction varies across tasks, model architectures, and dataset characteristics, hindering reproducibility and method development. We present DANCE 2.0, an automated and interpretable preprocessing platform featuring two key modules: the Method-Aware Preprocessing (MAP) module, which discovers optimal pipelines for task-specific methods via hierarchical search, and the Dataset-Aware Preprocessing (DAP) module, which recommends pipelines for new datasets via similarity-based matching to a reference atlas. Together, MAP and DAP execute over 325,000 pipeline searches across six major tasks - clustering, cell type annotation, imputation, joint embedding, spatial domain identification, and cell type deconvolution - yielding robust and generalizable recommendations. MAP-recommended pipelines consistently outperform original method defaults, with substantial gains across all tasks. Beyond automation, DANCE 2.0 reveals interpretable preprocessing patterns across tasks, methods, and datasets, transforming preprocessing into a transparent, data-driven process. All resources are openly available at https://github.com/OmicsML/dance to support broad community adoption and future methodological advances.

bioinformatics↗