Biology subjects

Cao, F.

Publications and source records attributed to Cao, F..

At least 19 recordsLinked to original sources

bioRxiv2026

Spike Sorting with VanillaSort

Training spike detectors on real recordings is challenging because algorithmically generated labels can be noisy and incomplete. We propose VanillaSort, combining multichannel detection with spatially augmented, template-guided clustering. VanillaDet uses visibility-aware masking, truncated Gaussian targets and a temporally tolerant positive-bag loss, followed by conditional event-SNR gating. VanillaCluster combines HuiduRep embeddings with relative-amplitude features for Gaussian mixture clustering and refines assignments using cross-fitted waveform templates built from selected core events. VanillaDet improves detection accuracy over SimSort by two and three percentage points on the static and drift subsets of Hybrid Janelia, respectively. The complete pipeline also improves sorting performance over the corresponding HuiduRep baselines. These results support learning from imperfect real-data labels and incorporating waveform consistency into neuronal assignment.

neuroscience↗

bioRxiv2026

Temporal single-cell profiling of the parabrachial Calca neurons reveals molecular dynamics driving nociplastic pain

Parabrachial Calca neurons are necessary for chronic pain and sufficient to drive nociplastic pain in mice, but how they sustain a pain state that outlasts its trigger is unknown. We performed temporal single-cell mRNA sequencing of the parabrachial nucleus (PBN) across the onset, chronic, and recovery phases of Calca neuron-driven tactile allodynia, using fixed-tissue profiling and reference-atlas registration to track molecularly defined populations over time. Activation broadly induced immediate-early genes, after which Calca neurons displayed changes in expression of genes that affect signaling and synaptic plasticity, with bidirectional changes that mirrored the onset and resolution of allodynia. The gene encoding brain-derived neurotrophic factor (Bdnf) remained persistently elevated in the chronic phase. BDNF infusion in the PBN prolonged allodynia, whereas blockade of its receptor (TrkB) attenuated it, and inactivating the Bdnf gene in Calca neurons abolished their hyperexcitability, attenuated allodynia, and relieved pain in a migraine model. These observations pinpoint BDNF as a driver of persistent nociplastic pain.

neuroscience↗

bioRxiv2026

A stickiness scale for disordered proteins

Disordered proteins are a heterogeneous group of proteins that play a broad range of functions in biology, and display conformational properties that range from compact globules to expanded chains. We here describe the results of a data-driven approach to derive a scale that represents the propensity of the twenty amino acids to interact with one another relative to water. The scale is based on biophysical experiments on 115 proteins and can be thought of as a stickiness (or hydropathy) scale specific for disordered proteins. We compare the scale to 70 other previously reported hydropathy scales and find that it is closer to four scales related to membrane proteins or the transition temperatures of elastin-like peptides. We envisage that the new scale will be useful in bioinformatics and machine learning approaches to quantify the role of sequence composition and patterning in disordered proteins, to understand the driving forces for their interactions with other molecules, and their evolutionary conservation.

biophysics↗

bioRxiv2026

Multi-Omics Reveals Activated Fibroblasts with Dual Functional Roles in Repair and Negative Barrier in the CD8+ T Cell Cytotoxic Niche for Lung Cancer Neoadjuvant Therapy

A major challenge in elucidating immune activation and tolerance is that single-omics technologies are inherently limited. Since single-cell transcriptomics lacks spatial information and spatial transcriptomics lacks resolution or depth, neither can adequately model the multidimensional tumor immune microenvironment (TiME) features. We present NICHE (Niche Integrated Cellular Heterogeneity Elucidator), an integrative multi-omics framework. By aligning physical cell-cell interactions with single-cell ligand-receptor (L-R) expression, NICHE leverages single-cell transcriptomics, spatial proteomics, and AI modeling to systematically decode the composition, spatial interactions, and communications within immune functional niches. To validate NICHEs capabilities, we applied it to human tonsil tissue. The framework successfully identified key structural and functional units and deeply elucidated the cell-cell interactions and molecular crosstalk within them. Furthermore, these results were validated through orthogonal methods, including single-cell spatial transcriptomics and multiplexed immunofluorescence, which confirmed the accuracy and reproducibility of our analyses. In non-small cell lung cancer (NSCLC) patients undergoing neoadjuvant immunotherapy, CD8+ T cell cytotoxic niches mediate tumor clearance with variable outcomes, to define the cellular and molecular drivers behind this functional spectrum, we utilized NICHE to analyze the TiME from patients with complete versus partial pathological response, both pre- and post-treatment. We found that neoadjuvant immunotherapy may induce the activation of CXCL12+, NECTIN2+, POSTN+, and COL6A1+ fibroblasts through the activation of cytotoxic T cells. Paradoxically, these fibroblasts support tissue repair but also establish an immunosuppressive niche that protects residual tumor cells, ultimately attenuating treatment efficacy. Our work establishes a multidimensional framework for dissecting dynamic immune activity, with direct implications for understanding tumor immunology and identifying novel therapeutic targets.

immunology↗

bioRxiv2025

A New Method for Optimal Placement of Tumor Treating Fields Electrodes

OverviewTumor Treating Fields (TTFields) provide a non-invasive treatment option for newly diagnosed glioblastoma. While optimization of electrode placement is important to increase treatment efficacy, clinical therapy planning is done using an undisclosed and proprietary software (NovoTAL(R)), which is clinically unvalidated. This study investigates a new computational approach for optimizing TTFields electrode placement and is compared to the current clinical standard. MethodsWe developed a new computational pipeline integrating patient-specific anatomical data to optimize electrode configurations in five representative glioblastoma cases with diverse tumor locations and sizes. Two optimization strategies were employed: one maximizing electric field intensity at the tumor, and another enhancing coverage of the adjacent brain while maintaining sufficient tumor intensity. Results were compared to electrode placements generated by NovoTAL(R). Additional simulations with artificial tumors assessed the effects of tumor size and location. ResultsOptimized electrode placements improved electric field intensity in tumors by 18%-34% compared to the clinical standard. Coverage-weighted optimizations provided broader field coverage without significantly compromising tumor intensity. Smaller or surface-adjacent tumors benefited most from optimization, achieving precise targeting and enhanced coverage. Extensive randomized placement analyses highlighted the superior performance of the optimized configurations. Analysis of artificial models showed consistent improvements across varying tumor locations and sizes. ConclusionPersonalized optimization of TTFields electrode placement significantly improves electric field targeting of tumors and adjacent brain regions. This approach outperforms standardized planning software and clinical practices and supports future development of adaptive, automated strategies for individualized TTFields therapy in glioblastoma. Keypoints- Optimized TTFields array placement enhanced field intensity by 18-34% vs. clinical standard. - Optimized TTFields planning improved field coverage in tumor-adjacent regions. - Optimized TTFields planning outperformed standard methods and random placement. Importance of the studyTTFields are increasingly used as adjuvant therapy for glioblastoma. However, current individualized treatment planning relies on proprietary, undisclosed, and clinically unvalidated software, limiting transparency, optimization, and innovation in the field. This study introduces an individualized, semi-automated, and open-source method for optimal electrode placement based on standard MRI data, addressing a critical need for validated and adaptable planning tools. Our approach increased field intensity in tumors by 18-34% and achieved broader coverage compared to the standard clinical tool (NovoTAL(R)), without compromising therapeutic strength. Notably, the method also consistently outperformed extensive random electrode placements across diverse tumor types and sizes, highlighting its robustness and ability to achieve true optimal configurations. Open-source availability enhances reproducibility and clinical translation, representing a significant step toward more effective, individualized TTFields therapy. This advancement has the potential to improve outcomes for glioblastoma patients and underscores the importance of technology validation in neuro-oncology.

neuroscience↗

bioRxiv2025

A Novel 3D Visualization Method in Mice Identifies the Periportal Lamellar Complex (PLC) as a Key Regulator of Hepatic Ductal and Neuronal Branching Morphogenesis

The liver is a complex organ responsible for multiple functions, including metabolism, energy storage, detoxification, bile secretion, and immune regulation. Its highly organized vascular system plays a crucial role in maintaining functional zonation and tissue homeostasis. Within the liver, the hepatic artery, portal vein, hepatic vein, bile duct, and nerve networks intertwine to form an intricate three-dimensional architecture; however, traditional two-dimensional imaging fails to reveal their true spatial relationships, and current three-dimensional imaging methods remain insufficient to capture fine structural details. To achieve comprehensive visualization of these multi-ductal systems, we established a high-resolution three-dimensional imaging platform that combines multicolor perfusion of metallic compound nanoparticles (MCNPs) with an optimized tissue-clearing protocol (Liver-CUBIC), enabling simultaneous 3D reconstruction of the portal vein, hepatic artery, bile duct, and hepatic vein in mouse livers. Based on these data, we identified and defined a previously unrecognized structure located in the outer layer of the portal vein, termed the Periportal Lamellar Complex (PLC). The PLC encircles the portal vein between the vascular endothelium and the perisinusoidal region, exhibits low-permeability barrier characteristics, and contains a distinctive population of CD34Sca-1 endothelial cells. During liver fibrosis, the PLC extends from the portal vein toward the hepatic lobule, forming a structural scaffold that guides bile duct and nerve migration.

developmental biology↗

bioRxiv2025

HuiduRep: A Robust Self-Supervised Framework for Learning Neural Representations from Extracellular Recordings

Extracellular recordings are transient voltage fluctuations in the vicinity of neurons, serving as a fundamental modality in neuroscience for decoding brain activity at single-neuron resolution. Spike sorting, the process of attributing each detected spike to its corresponding neuron, is a pivotal step in brain sensing pipelines. However, it remains challenging under low signal-to-noise ratio (SNR), electrode drift, and cross-session variability. In this paper, we propose HuiduRep, a robust self-supervised representation learning framework that extracts discriminative and generalizable features from extra-cellular recordings. By integrating contrastive learning with a denoising autoencoder, HuiduRep learns latent representations robust to noise and drift. With HuiduRep, we develop a spike sorting pipeline that clusters spike representations without ground truth labels. Experiments on hybrid and real-world datasets demonstrate that HuiduRep achieves strong robustness. Furthermore, the pipeline outperforms state-of-the-art tools such as KiloSort4 and MountainSort5. These findings demonstrate the potential of self-supervised spike representation learning as a foundational tool for robust and generalizable processing of extracellular recordings.

bioinformatics↗

bioRxiv2025

Granulin+ macrophages promote lineage plasticity in prostate cancer through paracrine signaling loops

The role of tumor-infiltrating immune cells in driving phenotype switching remains unclear, despite the well-established association between lineage transition and drug resistance in prostate cancer. This study employed an integrated analysis of single-cell multiomics to investigate the dynamics of immune infiltration, transcriptional programs, and cell-cell communication in prostate cancer. Our results demonstrated that granulin (GRN) positive macrophages facilitated the transition from adenocarcinoma to a multilineage state with mesenchymal and stem-like traits by activating intra-tumoral NF-{kappa}B signaling. Subsequently, the multilineage clones induced macrophages to highly express granulin through the secretion of CSF1, forming a positive feedback cell communication loop. Next, we validated the biological function of granulin in mediating epithelial-mesenchymal transition in vitro. Additionally, organoids drug resistance assay demonstrated that granulin drove resistance to androgen receptor (AR)-targeted drug (enzalutamide). Moreover, pharmacologic blockade of the CSF-1/CSF-1R axis in TRAMP mouse models reduced the expression of GRN in macrophages and suppressed the formation of multilineage subclones in prostate malignant cells. Furthermore, multiplex immunofluorescence staining of tumor samples from TRAMP mouse models revealed the VIM lineages were spatially in close contact with macrophages. Meanwhile, Cytometry by Time-Of-Flight (CyTOF) analysis validated our findings at single-cell protein level in patients with castration-resistant prostate cancer. Besides, three distinct tumor-infiltrating subsets associated with disease relapse were identified, including DCN+ endothelial cells, CCL7+ fibroblasts, and IFIT1+ neutrophils. These results offer potential therapeutic targets to address lineage plasticity-driven resistance to AR-targeted therapy.

cancer biology↗

bioRxiv2025

GPX4 Promotes Optic Nerve Regeneration and RGC Neuroprotection

Preventing retinal ganglion cells (RGCs)s soma and axon degeneration and promoting optic nerve (ON) regeneration holds great promise for effective glaucoma treatment. To explore potential neural repair strategies, we focused on glutathione peroxidase 4 (GPX4), a key regulator of lipid peroxidation. GPX4 is upregulated in surviving RGCs after acute ON crush or chronic ocular hypertension insult, and also in regenerating RGCs. AAV-mediated RGC-specific overexpression of GPX4 promotes significant ON regeneration and RGC survival, along with visual functional preservation, demonstrating the detrimental role of lipid peroxidation in glaucoma and the therapeutic potential of modulating lipid peroxidation through GPX4 in optic neuropathies.

neuroscience↗

bioRxiv2025

The HORMA-domain protein ASY1 recruits the plant-specific cyclin SDS to promote DMC1-mediated meiotic recombination

The chromosome axis is a proteinaceous scaffold essential for crossover formation in meiosis. While the axis associated HORMA-domain protein ASY1 is known to be necessary for the localization of the recombinase DMC1 to the axis, the molecular mechanism linking ASY1 to DMC1 loading remains unclear. Here, we demonstrate that ASY1 directly recruits the plant-specific cyclin SDS to chromosomes, which ensures efficient DMC1 localization and interhomolog recombination. Live-cell imaging and immunodetection revealed that SDS localizes to chromosomes from leptotene to zygotene and dissociates from chromosomes after pachytene resembling DMC1 dynamics. Biochemical assays demonstrated a direct interaction between ASY1 and SDS. Further analyses revealed that ASY1s closure motif, a conformational regulatory element, is required for SDS recruitment despite being dispensable for ASY1s own chromosome association. Moreover, unlike in sds mutants, depletion of the DMC1 inhibitor FIGL1-FLIP complex failed to restore DMC1 foci in asy1 mutants, positioning ASY1 upstream of both positive (SDS) and negative (FIGL1-FLIP) regulators of DMC1. These findings establish ASY1 as a key coordinator of meiotic recombination, bridging chromosome axis architecture with recombinase dynamics to control crossover formation and genome stability.

plant biology↗

bioRxiv2025

Local, but not circulating, complement C3 governs immune checkpoint blockade efficacy

The roles of circulating complement C3, produced in hepatocytes, in immune defense are well defined in the literature. Interestingly, the C3 gene evolved before the circulatory system, suggesting an essential but yet unknown role of locally produced C3. Here, we investigated the effect of C3 on cancer immunotherapy and found that cancer-associated fibroblast (CAF)-derived C3, not hepatocyte-derived C3, determines the efficacy of immune checkpoint blockade (ICB). Tumors developed in CAF-specific C3 knockout mice exhibited resistance to anti-PD-1 therapy, with increased immunosuppressive M2-like macrophage infiltration. Mechanistically, the C3 degradation product iC3b suppressed myeloid cell infiltration via complement receptor 3 signaling, and the therapeutic targeting of this pathway restored ICB sensitivity of immunotherapy-resistant tumors. In human cancers, stromal C3 expression correlates with reduced M2-like macrophage infiltration and improved immunotherapeutic outcomes. These data demonstrate the role of locally produced C3 in the innate immune response, which may have been conserved across many organisms.

cancer biology↗

bioRxiv2025

Identification of actionable targeted protein degradation effector sites through Site-specific Ligand Incorporation-induced Proximity (SLIP)

Targeted protein degradation (TPD) is a rapidly emerging and potentially transformative therapeutic modality. However, the large majority of >600 known ubiquitin ligases have yet to be exploited as TPD effectors by proteolysis-targeting chimeras (PROTACs) or molecular glue degraders (MGDs). We report here a chemical-genetic platform, Site-specific Ligand Incorporation-induced Proximity (SLIP), to identify actionable ("PROTACable") sites on any potential effector protein in intact cells. SLIP uses genetic code expansion (GCE) to encode copper-free "click" ligation at a specific effector site in intact cells, enabling in situ formation of a covalent PROTAC-effector conjugate against a target protein of interest (POI). Modification at actionable effector sites drives degradation of the targeted protein, establishing the potential of these sites for TPD. Using SLIP, we systematically screened dozens of sites across E3 ligases and E2 enzymes from diverse classes, identifying multiple novel potentially PROTACable effector sites which are competent for TPD. SLIP adds a powerful approach to the proximity-induced pharmacology (PIP) toolbox, enabling future effector ligand discovery to fully enable TPD, and other emerging PIP modalities.

molecular biology↗

bioRxiv2024

Fast FEM-based Electric Field Calculations for Transcranial Magnetic Stimulation

ObjectiveTo provide a Finite-Element Method (FEM) for rapid, repeated evaluations of the electric field induced by transcranial magnetic stimulation (TMS) in the brain for changing coil positions. ApproachPreviously, we introduced a first-order tetrahedral FEM enhanced by super- convergent patch recovery (SPR), striking a good balance between computational efficiency and accuracy (Saturnino et al 2019 J. Neural Eng. 16 066032). In this study, we refined the method to accommodate repeated simulations with varying TMS coil position. Starting from a fast direct solver, streamlining the pre- and SPR-based post-calculation steps using weight matrices computed during initialization strongly improved the computational efficiency. Additional speedups were achieved through efficient multi-core and GPU acceleration, alongside the optimization of the volume conductor model of the head for TMS. Main ResultsFor an anatomically detailed head model with [~]4.4 million tetrahedra, the optimized implementation achieves update rates above 1 Hz for electric field calculations in bilateral gray matter, resulting in a 60-fold speedup over the previous method with identical accuracy. An optimized model without neck and with adaptive spatial resolution scaled in dependence to the distance to brain grey matter, resulting in [~]1.9 million tetrahedra, increased update rates up to 10 Hz, with [~]3% numerical error and [~]4% deviation from the standard model. Region-of-interest (ROI) optimized models focused on the left motor, premotor and dorsolateral prefrontal cortices reached update rates over 20 Hz, maintaining a difference of <4% from standard results. Our approach allows efficient switching between coil types and ROI during runtime which greatly enhances the flexibility. SignificanceThe optimized FEM enhances speed, accuracy and flexibility and benefits various applications. This includes the planning and optimization of coil positions, pre-calculation and training procedures for real-time electric field simulations based on surrogate models as well as targeting and dose control during neuronavigated TMS.

neuroscience↗

bioRxiv2024

Tag with Caution - How protein tagging influences the formation of condensates

Fluorescent proteins and peptide tags are essential tools in cellular biology, but can alter the biochemical properties of target proteins. Biomolecular condensates, which have emerged as key principles of cellular organization, are suggested to provide robustness to cells, yet they can also respond sensitively to small changes in environmental conditions--or tagging of their components, as our findings suggest. Here, we investigated the effects of sixteen widely used tags on condensate formation in various model organisms, in vitro, in cells and by computational modelling. We find that tagging strongly influenced condensation for some proteins, while others remained unaffected. Effects varied, with some tags enhancing and others decreasing condensation, and depended on the protein being tagged. Coarse-grained simulations suggest that the charge of the fluorescent protein tags is a critical factor modulating condensation behavior. Together, our results underscore the importance of rigorous experimental design and interpretation in condensate experiments.

molecular biology↗

bioRxiv2024

Pipeline for Assessing Tumor Immune Status Using Superplex Immunostaining and Spatial Immune Interaction Analysis

The characteristics of the tumor microenvironment (TME) are closely linked to tumor progression and treatment response. The TME comprises various cell types, their spatial distribution, cell-cell interactions, and their organization into cellular niches or neighborhoods. To capture this complexity, several spatial profiling technologies have been developed. However, challenges such as low throughput, high costs, and complicated data analysis have limited their widespread use in immune research. In this study, we introduce the Cyclic-multiplex TSA (CmTSA) staining platform, a high-throughput superplex staining technology based on tyramide signal amplification (TSA) immunostaining combined with an efficient fluorophore recycling method. The CmTSA platform allows for the labeling of 30-60 antigens across multiple parallel formalin-fixed paraffin-embedded (FFPE) slides. Furthermore, the automated CmTSA workflow requires only standard histological equipment and conventional immunohistochemistry (IHC) primary antibodies (Abs), significantly reducing costs. While the superplex images produced contain extensive multidimensional information, extracting the spatial features of the TME from raw pixel data can be challenging. To address this, we present a computer vision-based analysis pipeline, which begins with deep learning-based algorithms to segment individual cells and identify cell types based on defined annotation rules. It then evaluates the spatial distribution tendencies of each cell type, the interaction intensity between paired cells, and the multicellular functional niches. This comprehensive approach enables researchers to visualize and quantify the types, states, and levels of immune activities within the TME effectively, advancing tumor immunology research and precision immune medicine.

cancer biology↗

bioRxiv2024

Gustatory Thalamic Neurons Mediate Aversive Behaviors

The parvicellular part of the ventral posteromedial nucleus (VPMpc) of the thalamus, also known as the gustatory thalamus, receives input from the parabrachial nucleus and relays taste sensation to the gustatory (or insular) cortex. Prior research has focussed on the role of the VPMpc in relaying taste signals. Here we provide evidence showing that VPMpc also mediates aversive behaviors. By recording calcium transients in vivo from single neurons in mice, we show that neurons expressing cholecystokinin and the mu-opioid receptor in the VPMpc respond to various noxious stimuli and fear memory. Chemogenetic and optogenetic activation of these neurons enhances the response to aversive stimuli, whereas silencing them attenuates aversive behaviors. The VPMpc neurons directly innervate neurons in the insular cortex and rostral lateral amygdala. This study expands the role of the VPMpc to include mediating aversive and threating signals to the insular cortex and lateral amygdala.

neuroscience↗

bioRxiv2024

Bottom-up reconstruction of functional Death Domain Signalosomes reveals a requirement for polymer stability and avidity

A key feature of innate immune signaling is the compartmentalization of signaling effectors into cellular structures referred to as signalosomes. Critical to the formation of these compartments are protein polymers composed of Death Domains (DD). However, the biophysical properties these polymeric scaffolds require for signal transduction are not clearly defined. Here, we engineered a single-component signalosome, referred to as Chimeric Higher-order Assemblies for Receptor Mediated Signaling (CHARMS). We found that CHARMS functionality depends on the stability provided by the DD polymer, which could also be achieved with bacterial DDs and synthetic filament-forming domains. This demonstrates the importance of kinetic stability and inducibility, irrespective of the origin of the motif. By varying the multiplicity of TRAF6 interaction motifs, we demonstrate that avidity is a tunable property that can control the amplitude of signaling outputs. This work lays out a reductionist framework to dissect the required properties of signaling through polymeric scaffolds by adjusting their assembly kinetics, stability and avidity.

cell biology↗

bioRxiv2024

Parabrachial Calca neurons mediate second-order conditioning

Learning to associate cues, both directly and indirectly, with biologically significant events is essential for survival. Second-order conditioning (SOC) involves forming an association between a previously reinforced conditioned stimulus (CS1) and a new conditioned stimulus (CS2) without the presence of an unconditioned stimulus (US). The neural substrates mediating SOC, however, remain unclear. In the parabrachial nucleus, Calca gene-expressing neurons, which react to the noxious US, also respond to a CS after its pairing with a US. This observation led us to hypothesize their involvement in SOC. To explore this possibility, we established an aversive SOC behavioral paradigm in mice and monitored Calca neuron activity via single-cell calcium imaging during SOC and subsequent recall phases. These neurons were activated not only by CS1 following its association with the US but also by CS2 after SOC. Chemogenetically inhibiting these neurons during second-order associations attenuated SOC. These findings suggest that activating the US pathway in response to a learned CS plays an important role in forming the association between the old and a new CS, promoting the formation of second-order memories.

neuroscience↗