Biology subjects

Yue, S.

Publications and source records attributed to Yue, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Cholesteryl Ester as a Prognostic Biomarker In IDH-wildtype Glioblastoma

Current treatment of IDH-wildtype glioblastoma (GBM) relies on the first-line chemotherapy-temozolomide. Although MGMT methylation is routinely conducted to predict chemosensitivity, its efficacy is often compromised. Thus, there is an urgent need to discover more accurate prognostic biomarkers. Cholesteryl ester (CE) has been recently recognized as a key feature of GBM, however, its role in GBM prognosis remains poorly understood. We first employed label-free stimulated Raman scattering (SRS) imaging to quantitatively analyze CE level in intact tumor tissues obtained from IDH-wildtype GBM patients. Our result revealed significantly prolonged 2-year overall survival (OS) in patients with CE level [≥] 40% compared to those with CE level < 40%. CE outperformed MGMT methylation for 2-year OS prognosis (AUC: 0.836 vs. 0.763). Importantly, CE also achieved superior prognostic performance over MGMT methylation on an independent cohort, with higher sensitivity (0.856 vs. 0.667), specificity (0.833 vs. 0.583), NPV (1.00 vs. 0.667), PPV (0.833 vs. 0.583). Given synergistic effects between CE and MGMT methylation, we developed a prognostic model combining these two biomarkers. Specially, machine learning (XGBoost) model exhibited optimal performance in the training cohort (AUC: 0.920), and maintained its superior performance on the independent cohort (sensitivity: 0.946, specificity: 0.873, NPV: 1.00; PPV: 0.917). Mechanistically, integrative analysis of TCGA database linked poor prognosis to the coordinated upregulation of genes involved in cholesterol efflux, hydrolysis, transport, and inhibition of de novo synthesis, unraveling a possible underlying mechanism between poor prognosis and cholesterol metabolism. This work identified CE as a prognostic biomarker for IDH-wildtype GBM.

neuroscience↗

bioRxiv2026

Temporal Dissociation of Syntactic Disambiguation and Memory Retrieval during Sentence Processing: Naturalistic MEG Evidence from Interpretable Models

Human sentence comprehension proceeds word-by-word, with prior research proposing two central sources of cognitive demand during incremental processing: forward-looking disambiguation of the incoming information stream, and backward-looking retrieval of information associated with previous words from working memory. Recent work has shown that Transformer-based language models successfully generate predictions about sentence processing load in human psycho- and neurolinguistic data by operationalizing disambiguation cost as next-token surprisal, and memory retrieval cost as normalized attention entropy (NAE). Such models, however, remain difficult to interpret as it is not well understood what factors play causally into the decision to assign a cost value to a given word in such artificial neural networks. Here, we present interpretable and cognitively grounded models of disambiguation and memory retrieval and evaluate their neural alignment and spatio-temporal correlates using human magnetoencephalography responses to naturalistic narrative speech. Multivariate temporal response function modeling demonstrates firstly that these human-bias-informed models fare equally well in accounting for observed human language processing data as their Transformer counterparts. This same modeling framework then suggests that surprisal and NAE temporally dissociate in the cortical language network -- surprisal being predictive of bilateral superior temporal gyrus and supramarginal gyrus activation [~]300-500 ms, and NAE being predictive of activity in the same regions, but later [~]750-850 ms. By demonstrating that interpretable neurocomputational models can achieve meaningful brain alignment while maintaining explanatory transparency, this work offers a methodological blueprint for bridging the gap between algorithmic theory and neural implementation.

neuroscience↗

bioRxiv2025

Analysis of Nutritional Components in Brown Sugar and Its Effects on Anti-fatigue, Alleviation of Qi Deficiency and Blood Stasis, and Antioxidant Effects

Brown sugar (BS), Red granulated sugar (RGS) and White sugar(WS) are three key sweeteners and food additives in China. Notably, BS possesses significant nutritional value and has been widely used in Chinese medicine for its supportive therapeutic properties.This study evaluated the anti-fatigue, the amelioration of qi deficiency and blood stasis, as well as the antioxidant activities of these sugars using a zebrafish model. BS and RGS demonstrated significantly greater efficacy than WS in terms of both anti-fatigue effects and amelioration of qi Deficiency and blood stasis in the zebrafish model. Antioxidant assays revealed that BS, RGS, and WS (500 g/mL) significantly enhanced superoxide dismutase (SOD) activity in zebrafish embryos compared with the control group. Furthermore, the mineral composition of sugar were determined. Nine mineral elements--potassium (K), calcium (Ca), sodium (Na), magnesium (Mg), iron (Fe), zinc (Zn), copper (Cu), phosphorus (P), and selenium (Se)--were analyzed. BS exhibited markedly higher concentrations of P, Ca, Fe, and Mg than RGS and WS, while selenium (detected at 50 mg/kg) was exclusively detected in BS. Intriguingly, RGS contained four-fold higher potassium levels than BS. Total polyphenol content, quantified by Folin-Ciocalteu assay, was 4.35 g/kg in BS and 1.53 g/kg in RGS, with no detectable polyphenols in WS.

biochemistry↗

bioRxiv2025

Embryonic Durotaxis: A Mechanical Framework for Understanding Cesarean Scar Pregnancy

Cesarean scar pregnancy (CSP) is an increasingly common complication associated with the rise in cesarean section rates, yet its underlying mechanisms remain poorly understood. In this study, we identified a stiffness gradient between healthy and scarred uterine tissues in both human cesarean samples and mouse uterine scar models. By employing gradient stiffness hydrogels, we demonstrated that mouse embryos and human trophoblast spheroids exhibit durotaxis, migrating preferentially toward stiffer areas. This migration occurs through three-dimensional complex behaviors--translation, swinging, and rolling--characterized by periodic patterns that align with cavity oscillations. Embryonic durotaxis is initiated from asymmetric adhesion forces and is driven by embryonic protrusive forces, generated from Marangoni-like tissue flows. The intrinsic cavity oscillations further amplify and sustain embryonic durotaxis. Finally, pharmacological inhibition of embryonic durotaxis significantly reduced CSP incidence in the mouse model. Our findings establish the concept of embryonic durotaxis, which may provide novel therapeutic avenues for CSP prevention.

developmental biology↗

bioRxiv2024

I2Bot: an open-source tool for multi-modal and embodied simulation of insect navigation

Achieving a comprehensive understanding of animal intelligence demands an integrative approach that acknowledges the interplay between an organisms brain, body, and environment. Insects like ants, despite their limited computational resources, demonstrate remarkable abilities in navigation. Existing computational models often fall short in faithfully replicating the morphology of real insects and their interactions with the environment, hindering validation and practical application in robotics. To address these gaps, we present I2Bot, a novel simulation tool based on the morphological characteristics of desert ants. This tool empowers robotic models with dynamic sensory capabilities, realistic modelling of insect morphology, physical dynamics, and sensory capacity. By integrating gait controllers and computational models into I2Bot, we have implemented classical embodied navigation behaviours and revealed some fundamental navigation principles. By open-sourcing I2Bot, we aim to accelerate the understanding of insect intelligence and foster advances in the development of autonomous robotic systems.

animal behavior and cognition↗

bioRxiv2023

Artificial intelligence-assisted stimulated Raman molecular cytology enables accurate and rapid intraoperative assessment of the surgical margin in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly mortal cancer whose only potentially curative treatment is surgical resection. Intraoperative assessment of its surgical margins is vital for patient survival. Frozen-section biopsy is routinely performed for this purpose. However, its high dependence on pathologists experience frequently poses diagnostic discrepancies. The essential invasiveness of PDAC also causes sampling errors. This study developed an intelligent molecular cytology approach with improved diagnostic objectivity and broader sampling coverage. Our method, Multi-Instance Cytology with Learned Raman Embedding (MICLEAR), is characterized by compositional information provided by label-free Raman imaging. First, 4085 cells were brushed off from the pancreases of 41 patients and imaged using stimulated Raman scattering microscopy. Then, a contrastive learning-based cell embedding model was developed to compress each cells morphological and compositional information into a compact cell vector. Finally, a multi-instance learning-based diagnosis model using cell vectors was employed to predict the likelihood of a patients margin being positive. MICLEAR achieved 80% sensitivity, 94.1% specificity, and an AUC of 0.86 on 27 patients for validation, comprising 10 with positive margins and 17 with negative ones, within approximately 8 minutes per patient. It may hold promises for more efficient and accurate intraoperative assessment of PDAC surgical margins.

biophysics↗

bioRxiv2023

A resource for probing influences of perinatal factors on neurodevelopment in 3-10-years-old Chinese children

Adverse perinatal factors can disrupt the normal development of the brain, with potential long-term impacts on childrens overall development. Currently, the neuropathological mechanisms by which these factors lead to various neurodevelopmental disorders (NDDs) remain largely unknown. An open resource that integrate perinatal factors with brain and mental health development is essential for investigating NDD-related aetiology. In this Data Descriptor, we introduce a multicentre database containing information on perinatal factors that influence childrens brain-mind development, namely, periCBD, that combines neuroimaging and behavioural phenotypes with perinatal factors associated with a high incidence of NDDs at county/region/central district hospitals. PeriCBD was designed to establish a platform for the investigation of individual differences in brain-mind development among children aged 3-10 years are associated with perinatal factors. Ultimately, our goal was to develop an early prediction and screening model for NDDs that leverages normative data to facilitate NDD aetiology research. Herein, we provide a systematic overview of the data acquisition/cleaning/quality control/sharing, processes of periCBD and present preliminary brain-mind associations.

neuroscience↗

bioRxiv2023

VHL Mutation Drives Human Clear Cell Renal Cell Carcinoma Progression Through PI3K/AKT-Dependent Cholesteryl Ester Accumulation

BackgroundCholesteryl ester (CE) accumulation in intracellular lipid droplets (LDs) is an essential signature of clear cell renal cell carcinoma (ccRCC), but its molecular mechanism and pathological significance remain elusive. MethodsEnabled by the label-free Raman spectromicroscopy, which integrated stimulated Raman scattering microscopy with confocal Raman spectroscopy on the same platform, we quantitatively analyzed LD distribution and composition at the single cell level in intact ccRCC cell and tissue specimens in situ without any processing or exogenous labeling. Since we found that commonly used ccRCC cell lines actually did not show the CE-rich signature, primary cancer cells were isolated from human tissues to retain the lipid signature of ccRCC with CE level as high as the original tissue, which offers a preferable cell model for the study of cholesterol metabolism in ccRCC. Moreover, we established a patient-derived xenograft (PDX) mouse model that retained the CE-rich phenotype of human ccRCC. FindingsSurprisingly, our results revealed that CE accumulation was induced by tumor suppressor VHL mutation, the most common mutation of ccRCC. Moreover, VHL mutation was found to promote CE accumulation by upregulating HIF and subsequent PI3K/AKT/mTOR/SREBPs pathway. Inspiringly, inhibition of cholesterol esterification remarkably suppressed ccRCC aggressiveness in vitro and in vivo with negligible toxicity, through the reduced membrane cholesterol-mediated downregulations of integrin and MAPK signaling pathways. InterpretationCollectively, our study improves current understanding of the role of CE accumulation in ccRCC and opens up new opportunities for treatment. FundingThis work was supported by National Natural Science Foundation of China (No. U23B2046 and No. 62027824), National Key R&D Program of China (No. 2023YFC2415500), Fundamental Research Funds for the Central Universities (No. YWF-22-L-547), PKU-Baidu Fund (No. 2020BD033), Peking University First Hospital Scientific and Technological Achievement Transformation Incubation Guidance Fund (No.2022CX02), and Beijing Municipal Health Commission (No. 2020-2Z-40713).

cancer biology↗

bioRxiv2023

Accurate and Rapid Detection of Peritoneal Metastasis from Gastric Cancer by AI-assisted Stimulated Raman Cytology

Peritoneal metastasis (PM) is the most common form of distant metastasis and one of the leading causes of death in gastric cancer (GC). For locally advanced GC, clinical guidelines recommend peritoneal lavage cytology for intraoperative PM detection. Unfortunately, current peritoneal lavage cytology is limited by low sensitivity (<60%). Here we established the stimulated Raman cytology (SRC), a chemical microscopy-based intelligent cytology. By taking advantages of stimulated Raman scattering in label-free, high-speed, and high-resolution chemical imaging, we firstly imaged 53951 exfoliated cells in ascites obtained from 80 GC patients (27 PM positive, 53 PM negative), at the Raman bands corresponding to DNA, protein, and lipid, respectively. Then, we revealed 12 single cell features of morphology and composition that were significantly different between PM positive and negative specimens, including cellular area, lipid protein ratio, etc. Importantly, we developed a single cell phenotyping algorithm to further transform the above raw features to feature matrix. Such matrix was crucial to identify the significant marker cell cluster, the divergence of which was finally used to differentiate the PM positive and negative. Compared with histopathology, the gold standard of PM detection, our SRC method assisted by machine learning classifiers could reach 81.5% sensitivity, 84.9% specificity, and the area under receiver operating characteristic curve of 0.85, within 20 minutes for each patient. Such remarkable improvement in detection accuracy is largely owing to incorporation of the single-cell composition features in SRC. Together, our SRC method shows great potential for accurate and rapid detection of PM from GC.

biophysics↗

bioRxiv2022

Coupling of perinuclear actin cap and nuclear mechanics regulates flow-induced YAP spatiotemporal nucleocytoplasmic transport

Mechanical forces, including flow shear stress, regulate fundamental cellular process by modulating the nucleocytoplasmic transport of transcription factors, such as Yes-associated Protein (YAP). However, the mechanical mechanism how flow induces the nucleocytoplasmic transport remains largely unclear. Here we found that unidirectional flow applied to endothelial cells induces biphasic YAP nucleocytoplasmic transport with initial nuclear import, followed by nuclear export as perinuclear actin cap forms and nuclear stiffening in a dose and timing-dependent manner. In contrast, pathological oscillatory flow induces slight actin cap formation and nuclear softening, sustaining YAP nuclear localization. To explain the disparately spatiotemporal distribution of YAP, we developed a three-dimensional mechanochemical model considering coupling processes of flow sensing, cytoskeleton organization, nucleus mechanotransduction, and YAP spatiotemporal transport. We discovered that actin cap formation and nuclear stiffness alteration under flow synergically regulate nuclear deformation, hence governing YAP transport. Furthermore, we expanded our single cell model to a collective vertex framework and found that actin cap irregularities in individual cells under flow shear stress potentially induce topological defects and spatially heterogeneous YAP distribution in cellular monolayers. Our work unveils the unified mechanism of flow-induced nucleocytoplasmic transport, offering a universal linkage between transcriptional regulation and mechanical stimulation.

bioengineering↗

bioRxiv2022

Excited-state dynamics of the all-trans protonated retinal Schiff base in CRABPII-based rhodopsin mimics

The rhodopsin mimic is a chemically synthetized complex with the retinyl Schiff base (RSB) formed between protein and the retinal chromophore, which can mimic the natural rhodopsin-like protein. The artificial rhodopsin mimic is more stable and designable than the natural protein and hence has wider uses in photon detection devices. The mimic structure RSB, like the case in the actual rhodopsin-like protein, undergoes isomerization and protonation throughout the photoreaction process. As a result, understanding the dynamics of the RSB in the photoreaction process is critical. In this study, the transient absorption spectra (TAS) of three mutants of the cellular retinoic acid-binding protein II (CRABPII)-based rhodopsin mimic at PH = 3 were recorded, from which the related excited-state dynamics of the all-trans protonated RSB (AT-PRSB) were investigated. The transient fluorescence spectra (TFS) measurements are used to validate some of the dynamic features. We find that the excited-state dynamics of AT-PRSB in three mutants share a similar pattern that differs significantly from the dynamics of 15-cis PRSB (15C-PRSB) of the rhodopsin mimic in neutral solution. By comparing the dynamics across the three mutants, we discovered that the aromatic residues near the {beta}-ionone ring structure of the retinal may help stabilize the AT-PRSB and hence slow down its isomerization rate. Furthermore, from the three mutants, we find one protein with near-infrared fluorescence emission up to 688 nm, leading to further possible applications in sensing or bioimaging.

biochemistry↗

bioRxiv2021

A human monoclonal antibody potently pan-neutralizes SARS-CoV-2 VOCs by targeting RBD invariant sites

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of novel corona virus disease (COVID-19). The neutralizing monoclonal antibodies (mAbs) targeting the receptor binding domain (RBD) of SARS-CoV-2 are among the most promising strategies to prevent and treat COVID-19. However, SARS-CoV-2 variants of concern (VOCs) profoundly reduced the efficacies of most of mAbs and vaccines approved for clinical use. Herein, we demonstrated mAb 35B5 efficiently neutralizes both wild-type (WT) SARS-CoV-2 and VOCs, including B.1.617.2 (delta) variant, in vitro and in vivo. Cryo-electron microscopy (cryo-EM) revealed that 35B5 neutralizes SARS-CoV-2 by targeting a unique epitope that avoids the prevailing mutation sites on RBD identified in circulating VOCs, providing the molecular basis for its pan-neutralizing efficacy. The 35B5-binding epitope could also be exploited for the rational design of a universal SARS-CoV-2 vaccine.

immunology↗

bioRxiv2021

How the insect central complex could coordinate multimodal navigation

The central complex of the insect midbrain is thought to coordinate insect guidance strategies. Computational models can account for specific behaviours but their applicability across sensory and task domains remains untested. Here we assess the capacity of our previous model explaining visual navigation to generalise to olfactory navigation and its coordination with other guidance in flies and ants. We show that fundamental to this capacity is the use of a biologically-realistic neural copy-and-shift mechanism that ensures sensory information is presented in a format compatible with the insect steering circuit regardless of its source. Moreover, the same mechanism is shown to transfer cues from unstable/egocentric to stable/geocentric frames of reference providing a first account of the mechanism by which foraging insects robustly recover from environmental disturbances. We propose that these circuits can be flexibly repurposed by different insect navigators to address their unique ecological needs.

animal behavior and cognition↗

bioRxiv2021

Twelve-month specific IgG response to SARS-CoV-2 receptor-binding domain among COVID-19 convalescent plasma donors in Wuhan

To investigate the duration of humoral immune response in convalescent coronavirus disease 2019 (COVID-19) patients, we conduct a 12-month longitudinal study through collecting a total of 1,782 plasma samples from 869 convalescent plasma donors in Wuhan, China and test specific antibody responses. The results show that positive rate of IgG antibody against receptor-binding domain of spike protein (RBD-IgG) to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the COVID-19 convalescent plasma donors exceeded 70% for 12 months post diagnosis. The level of RBD-IgG decreases with time, with the titer stabilizing at 64.3% of the initial level by the 9th month. Moreover, male plasma donors produce more RBD-IgG than female, and age of the patients positively correlates with the RBD-IgG titer. A strong positive correlation between RBD-IgG and neutralizing antibody titers is also identified. These results facilitate our understanding of SARS-CoV-2-induced immune memory to promote vaccine and therapy development.

immunology↗

bioRxiv2020

An Assistive Computer Vision Tool to Automatically Detect Changes in Fish Behavior In Response to Ambient Odor

The analysis of fish behavior in response to odor stimulation is a crucial component of the general study of cross-modal sensory integration in vertebrates. In zebrafish, the centrifugal pathway runs between the olfactory bulb and the neural retina, originating at the terminalis neuron in the olfactory bulb. Any changes in the ambient odor of a fishs environment warrants a change in visual sensitivity and can trigger mating-like behavior in males due to increased GnRH signaling in the terminalis neuron. Behavioral experiments to study this phenomenon are commonly conducted in a controlled environment where a video of the fish is recorded over time before and after the application of chemicals to the water. Given the subtleties of behavioral change, trained biologists are currently required to annotate such videos as part of a study. This process of manually analyzing the videos is time-consuming, requires multiple experts to avoid human error/bias and cannot be easily crowdsourced on the Internet. Machine learning algorithms from computer vision, on the other hand, have proven to be effective for video annotation tasks because they are fast, accurate, and, if designed properly, can be less biased than humans. In this work, we propose to automate the entire process of analyzing videos of behavior changes in zebrafish by using tools from computer vision, relying on minimal expert supervision. The overall objective of this work is to create a generalized tool to predict animal behaviors from videos using state-of-the-art deep learning models, with the dual goal of advancing understanding in biology and engineering a more robust and powerful artificial information processing system for biologists.

animal behavior and cognition↗

bioRxiv2019

Modelling the Insect Navigation Toolkit: How the Mushroom Bodies and Central Complex Coordinate Guidance Strategies

Insect navigation arises from the coordinated action of concurrent guidance systems but the neural mechanisms through which each functions, and are then coordinated, remains unknown. We propose that insects require distinct strategies to retrace familiar routes (route-following) and directly return from novel to familiar terrain (homing) using different aspects of frequency encoded views that are processed in different neural pathways. We also demonstrate how the Central Complex and Mushroom Bodies regions of the insect brain may work in tandem to coordinate the directional output of different guidance cues through a contextually switched ring-attractor inspired by neural recordings. The resultant unified model of insect navigation reproduces behavioural data from a series of cue conflict experiments in realistic animal environments and offers testable hypotheses of where and how insects process visual cues, utilise the different information that they provide and coordinate their outputs to achieve the adaptive behaviours observed in the wild.

animal behavior and cognition↗

bioRxiv2019

AVDM: Angular Velocity Decoding Model Accounting for Visually Guided Flight Behaviours of the Bee

We present a new angular velocity estimation model for explaining the honeybees flight behaviours of tunnel centring and terrain following, capable of reproducing observations of the large independence to the spatial frequency and contrast of the gratings in visually guide flights of honeybees. The model combines both temporal and texture information to decode the angular velocity well. The angular velocity estimation of the model is little affected by the spatial frequency and contrast in synthetic grating experiments. The model is also tested behaviourally in Unity with the tunnel centring and terrain following paradigms. Together with the proposed angular velocity based control algorithms, the virtual bee navigates well in a patterned tunnel and can keep a certain distance from undulating ground with gratings in a series of controlled trials. The results coincide with both neuron spike recordings and behavioural path recordings of honeybees, demonstrating that the model can explain how visual motion is detected in the bee brain.\n\nAuthor summaryBoth behavioural and electro-physiological experiments indicate that honeybees can estimate the angular velocity of image motion in their retinas to control their flights, while the neural mechanism behind has not been fully understood. In this paper, we present a new model based on previous experiments and models aiming to reproduce similar behaviours as real honeybees in tunnel centring and terrain following simulations. The model shows a large spatial frequency independence which outperforms the previous model, and our model generally reproduces the wanted behaviours in simulations.

animal behavior and cognition↗

bioRxiv2018

aFARP-ChIP-seq, a convenient and reliable method for genome profiling in as few as 100 cells with a capability for multiplexing ChIP-seq

Much effort has been devoted to understand how chromatin modification regulates development and disease. Despite recent progress, however, it remains difficult to achieve high sensitivity and reliability of chromatin-immunoprecipitation-coupled deep sequencing (ChIP-seq) to map the epigenome and global transcription factor binding sites in cell populations of low cell abundance. We present a new Atlantis dsDNase-based technology, aFARP-ChIP-seq, that provides accurate profiling of genome-wide histone modifications in as few as 100 cells. By mapping histone lysine trimethylation (H3K4me3) and H3K27Ac in group I innate lymphoid cells from different tissues, aFARP-ChIP-seq uncovers potentially distinct active promoter and enhancer landscapes of several tissue-specific NK and ILC1. aFARP-ChIP-seq is also highly effective in mapping transcription factor binding sites in small number of cells. Since aFARP-ChIP-seq offers reproducible DNA fragmentation, it should allow multiplexing ChIP-seq of both histone modifications and transcription factor binding sites for low cell samples.

genomics↗