Biology subjects

Xue, T.

Publications and source records attributed to Xue, T..

At least 19 recordsLinked to original sources

bioRxiv2026

In situ Discovery of Immune Repertoire Reveals Antitumor Immunity and Therapeutic Antibodies

Spatial transcriptomics offers a glimpse into the immunology of tissues. However, limitations in spatial transcriptomics preclude the detection of highly diverse, low-abundance, and previously unknown sequences, including immune repertoires and microbiota. Here, we introduce Archimap, a spatial transcriptomic platform that simultaneously profiles spatial transcriptomes, immune repertoires, and microbiota from formalin-fixed paraffin-embedded (FFPE) tissues. Using Archimap, we profile the spatial localization of TCRs, BCRs, and the microbiota landscape in archived clinical tissues at single-cell resolution. Through comprehensive benchmarking, we validate Archimaps performance and fidelity. Archimap in situ assembles the immune complex and reconstructs the clonal evolution of antibodies. Together, Archimap shows the power of in situ discovery of functional immune repertoires for their antitumor immunity.

bioinformatics↗

bioRxiv2026

From Spectra to Digital Phenotypes: Wearable Multispectral Sensing for Precision Light and Green Space Exposure

Light is a modifiable determinant of health, yet real-world exposure assessment is often reduced to illuminance alone, lacks environmental context, or relies on privacy-sensitive sensing. We present SpectraVita, a low-cost, compact multispectral wearable that continuously samples 11 ultraviolet-to-near-infrared bands and, through a privacy-preserving pipeline without cameras or location tracking, produces interpretable digital phenotypes of lighting environment (natural vs. artificial and source type) and vegetation context alongside standard visual and non-visual light metrics. In extensive in-the-wild recordings spanning diverse scenes, times of day, weather conditions, and light sources, we observe distinctive spectral signatures that enable supervised models to achieve a macro-averaged F1 score of 0.988{+/-}0.004 for light-source classification and green-space detection in boundary-free environments. A sensor-derived normalized difference vegetation index (NDVI) emerges as an explainable, physically grounded marker linking natural light exposure and greenness. Robustness is supported by scenario-shift testing, image-segmentation validation, and mixed-environment experiments that demonstrate sensitivity to partial and transient exposures, as well as by longitudinal stationary monitoring and deployment in a cohort of thousands of participants capturing seasonal and behavioral variability. SpectraVita enables individualized, privacy-preserving, longitudinal monitoring of light and greenness exposure at scale, addressing a key measurement gap for precision and population health studies of daily photic environments.

bioengineering↗

bioRxiv2026

Distinct principles of genome compartmentalization in Drosophila and humans revealed by osmotic stress

The three-dimensional organization of eukaryotic genomes into compartments, topologically associating domains, and loops is mediated by architectural proteins whose organizational principles vary across species. In Drosophila, insulator proteins including Su(Hw) and the histone variant {gamma}H2Av form liquid-liquid phase separation (LLPS) condensates, yet how this phase separation capacity relates to genome compartmentalization has remained unclear. Here we use hyperosmotic stress to simultaneously displace architectural proteins from chromatin in both Drosophila and human cells, enabling a comparative dissection of genome organization principles across species. We find that although human CTCF shares predicted LLPS properties with Drosophila insulator proteins, it does not form condensates upon osmotic stress, while Drosophila insulator proteins do. Hi-C analysis reveals that osmotic stress causes loss of compartments, TAD boundary strength, and loops in both organisms, but genome recovery after stress is rapid and near-complete in human cells while remaining substantially incomplete in Drosophila after one hour. Analysis of this recovery asymmetry reveals a fundamental difference in compartment organization: whereas human A and B compartments engage in robust homotypic long-range interactions, Drosophila B compartments rarely participate in long-range B-to-B contacts, indicating that the Drosophila genome does not replicate canonical A/B compartment organization. Instead, Drosophila genome architecture is dominated by A-to-A interactions, and A compartments are specifically enriched in {gamma}H2Av and Su(Hw), with moderate enrichment of cohesin subunits. Furthermore, loops in Drosophila are mechanistically independent from compartments and TADs, recovering before compartment structure is restored, and are anchored by Su(Hw) and cohesin rather than by dCTCF. Together, these findings suggest that the LLPS properties of {gamma}H2Av and Su(Hw) underlie A compartment formation in Drosophila through a mechanism distinct from the heterochromatin-driven B compartment interactions that predominate in vertebrates, revealing fundamentally different organizational principles between fly and human genomes.

genomics↗

bioRxiv2025

Spatial genome reorganization is associated with chromosomal breakage regions and karyotype changes induced by programmed DNA elimination

Programmed DNA elimination (PDE) is a notable exception to genome integrity, characterized by significant DNA loss during development. In many nematodes, PDE is initiated by DNA double-strand breaks (DSBs), which lead to chromosome fragmentation and subsequent DNA loss. However, the mechanism of nematode programmed DNA breakage remains largely unclear. Interestingly, in the human and pig parasitic nematode Ascaris, no conserved motif or sequence structures are present at chromosomal breakage regions (CBRs), suggesting the recognition of CBRs may be sequence-independent. Using Hi-C, we revealed that Ascaris CBRs engage in three-dimensional (3D) interactions before PDE, indicating that physical contacts between break regions may contribute to the PDE process. The 3D interactions are established in both Ascaris male and female germlines, demonstrating inherent genome organization associated with the CBRs and to-be-eliminated sequences. In contrast, in the unichromosomal horse parasite Parascaris univalens, transient pairwise interactions between neighboring CBRs that will form the ends of future somatic chromosomes were observed only during PDE. Intriguingly, we found that Ascaris PDE, which converts 24 germline chromosomes into 36 somatic ones, induces specific compartmentalization changes. Remarkably, Parascaris PDE generates the same set of 36 somatic chromosomes, and the 3D compartment changes following PDE are consistent between the two species. Overall, our findings suggest that CBRs spatially demarcate the retained and eliminated DNA and may contribute to their spatial organization during Ascaris PDE. We also demonstrated that the 3D genome reorganization of the somatic chromosomes in these nematodes following PDE is evolutionary and developmentally conserved.

genomics↗

bioRxiv2025

Class A PBPs reinforce the septal cell wall following initial synthesis by SEDS-bPBP pairs during bacterial cytokinesis

Bacterial cytokinesis requires the coordinated action of septal peptidoglycan (PG) synthases to ensure efficient and accurate septum formation. Two major types of synthases contribute: SEDS-bPBP and bifunctional class A PBPs (aPBPs). How their activities are organized in space and time has remained unclear. Using Deinococcus radiodurans, which often contains both constricting and closed septa in the same cell, we show that septal PG synthesis proceeds through distinct steps at different regions. Primary synthesis at the leading edge by SEDS-bPBP pairs drives constriction, whereas aPBPs act later at the lagging edge and in closed septa to thicken the wall, enhance cross-linking, and reinforce septal integrity. At the single-molecule level, both synthase types move directionally to perform processive PG synthesis at distinct sites. We also observed spatiotemporal separation of SEDS-bPBP and aPBP synthases in Staphylococcus aureus, suggesting that secondary septal PG synthesis is a conserved mechanism securing successful cytokinesis.

microbiology↗

bioRxiv2025

The multiscale distribution of radiation-induced DNA damage and its impact on local genome structure

The three-dimensional genome structure is critical for the regulation of gene expression and repair of DNA damage. While previous work has characterized genome-wide sites of DNA damage caused by etoposide or nucleases, the distribution of double-strand breaks (DSBs) caused by external radiation and how these interact with the 3D genome organization is less well understood. Here, we measure the genomic landscape of radiation-induced DNA damage using END-seq in fibroblasts and lymphoblasts after exposure to 5 Gy X-rays. We identify frequently broken regions and investigate the 3D genome properties around these breaks with Hi-C data. We observe that the distribution of robust breaks correlates with transcriptional and chromatin features of the genome. Transcriptionally active and decondensed regions, such as chromosome 19, the A compartment, and topologically associating domain (TAD) boundaries, show pronounced break probability. We also find evidence of DSB-induced loop formation in the vicinity of frequent radiation-induced breaks. Our data reveal that pre-existing 3D genome architecture influences the distribution of radiation-induced DSBs and that these breaks reshape local chromatin landscapes.

genomics↗

bioRxiv2025

Screening of Cellular Senescence Related Genes as Biomarkers and Therapeutic Targets for Glioblastoma by Integrated Machine Learning

Glioblastoma (GBM) is an aggressive brain tumor with limited prognostic biomarkers and therapeutic targets. This study applied an integrated machine learning (IML) framework to discover cellular senescence (CS)-related gene biomarkers and candidate therapeutic targets in GBM. Using Gene Expression Omnibus (GEO) training and validation cohorts, 113 machine learning models across 11 algorithms were integrated to pinpoint CS-associated gene signatures. Differential expression analysis combined with overlap of a CellAge senescence gene set yielded 129 CS-related differentially expressed genes (DEGs). Functional enrichment of these DEGs highlighted pathways related to cellular senescence and cell cycle regulation (Gene Ontology and KEGG). A multivariate classifier constructed via stepwise generalized linear modeling (GLM) and LASSO achieved high diagnostic performance (area under the ROC curve 0.92 in training, each independent validation set is over 0.85). Seven top-ranked genes from this model were validated, with TGF{beta}I emerging as the most robust biomarker (AUC > 0.85) and its elevated expression was associated with significantly shorter overall survival. Spatial transcriptomics and single-cell RNA sequencing localized TGF{beta}I expression to tumor cell clusters harboring high copy number variation (CNV) burdens. Immune microenvironment profiling linked TGF{beta}I expression with increased macrophage infiltration. Finally, single-cell gene set enrichment (scGSEA) and AUCell analyses indicated enrichment of ECM-receptor interaction signaling in TGF{beta}I-expressing cells. In summary, IML combined with spatial and single-cell transcriptomics identified TGF{beta}I as a potent CS-related biomarker and a promising therapeutic target in GBM.

cancer biology↗

bioRxiv2025

The superficial white matter in language processing: Broca's area connections are bilaterally associated with individual performance in children and adults

While deeper white matter connections, such as the arcuate fasciculus and frontal aslant tract, are well known for their role in language and show leftward asymmetries in adults, the contribution of the short-range cortico-cortical superficial white matter (SWM) connections remains less understood. In this preregistered study, we examined white matter connections of Brocas area and its right hemisphere homolog in early adolescents and young adults using two large, publicly available datasets: the Adolescent Brain Cognitive Development Study and the Human Connectome Project Young Adult Study, totaling over 10,000 participants. We anatomically curated the ODonnell Research Group (ORG) tractography atlas to identify SWM fiber clusters intersecting Brocas area (pars opercularis and pars triangularis), confirmed through expert visual inspection. We investigated the microstructure, structural connectivity, and lateralization of Brocas area SWM and its relationship with language performance (Picture Vocabulary and Oral Reading Recognition assessments), in comparison to the deeper white matter connections of the frontal aslant tract and arcuate fasciculus. The arcuate fasciculus demonstrated the strongest and most consistent leftward lateralization of both microstructure (fractional anisotropy, FA) and structural connectivity (number of streamlines, NoS), with structure-function associations that were bilateral in adolescents and left-dominant in adults. Interestingly, despite weaker lateralization than the arcuate fasciculus, both the SWM and the frontal aslant tract demonstrated comparable associations with language performance. The frontal aslant tract showed greater leftward lateralization (FA and NoS) with age and was bilaterally associated with language performance, particularly in adolescents. Compared to these deeper tracts, Brocas area SWM demonstrated left-lateralized FA and right-lateralized NoS in both adolescents and adults, with stronger FA lateralization in adults. Bilateral SWM FA and NoS were significantly associated with language performance in both hemispheres and age groups. Overall, these results suggest that Brocas area SWM may support language in a more bilaterally distributed manner and highlight the importance of considering SWM connections in studies of language development and neurosurgical planning.

neuroscience↗

bioRxiv2025

Supervised and unsupervised machine learning methods for modelling current and future habitat of Peruvian anchovy

Understanding the drivers and potential impacts of environmental variability on the distribution of Peruvian anchovies, the largest single-species fishery on the planet, is essential for their proper management in a changing world. However, the intricate interactions of these organisms and environmental variability require the use of complex models such as machine learning methods. In this study, we compared three methods for producing habitat maps of anchovies: the traditional Generalised Additive Models, the XGBoost which is a form of supervised machine learning and a new method based on clustering water types as a form of unsupervised machine learning. We optimised the three methods with a parameter grid search algorithm and compared their capability to replicate the mean state of anchovies by comparing them with presence-absence observations along the Peruvian coastline between 1990 and 2010. We used the output of a physical-biogeochemical model as input for the habitat models to produce distribution maps of anchovy. All models successfully simulated the distribution of anchovies along the Peruvian coastline in normal years and a reduced area of distribution with most of the anchovies in the southern part of the domain during the canonical El Nino 97/98. We then applied the models to predict potential changes in the distribution of anchovies under projected temperature and wind conditions by the end of the century. We observed a reduction in the probability of anchovy occurrence under conditions of higher temperature and weaker winds. Two of the three habitat models predicted a severe maximum decline by 90% (GAM) and 75% (XGBoost) whereby the clustering model predicted a moderate maximum decline in anchovy occurrence by 20%.

ecology↗

bioRxiv2025

Integrative Machine Learning and Bioinformatics Analysis to Identify Cellular Senescence-Related Genes and Potential Therapeutic Targets in Ulcerative Colitis and Colorectal Cancer

BackgroundUlcerative colitis (UC) is a chronic inflammatory condition that predisposes patients to colorectal cancer (CRC) through mechanisms that remain largely undefined. Given the pivotal role of cellular senescence in both chronic inflammation and tumorigenesis, we integrated machine learning and bioinformatics approaches to identify senescence{square}related biomarkers and potential therapeutic targets involved in the progression from UC to CRC. MethodsGene expression profiles from six GEO datasets were analyzed to identify differentially expressed genes (DEGs) using the limma package in R. Weighted gene co expression network analysis (WGCNA) was employed to delineate modules significantly associated with UC and CRC, and the intersection of DEGs, key module genes, and senescence related genes from the CellAge database yielded 112 candidate genes. An integrated machine learning (IML) model, utilizing 12 algorithms with 10 fold cross validation was constructed to pinpoint key diagnostic biomarkers. The diagnostic performance of the candidate genes was evaluated using receiver operating characteristic (ROC) analyses in both training and validation cohorts. In addition, immune cell infiltration, protein protein interaction (PPI) networks, and drug enrichment analyses, including molecular docking were performed to further elucidate the biological functions and therapeutic potentials of the identified genes. ResultsOur analysis revealed significant transcriptomic alterations in UC and CRC tissues, with the turquoise module demonstrating the strongest association with disease traits. The IML approach identified five pivotal genes (ABCB1, CXCL1, TACC3, TGFBI, and VDR) that individually exhibited AUC values >0.7, while their combined diagnostic model achieved an AUC of 0.989. Immune infiltration analyses uncovered distinct immune profiles correlating with these biomarkers, and the PPI network confirmed robust interactions among them. Furthermore, drug enrichment and molecular docking studies identified several promising therapeutic candidates targeting these senescence{square}related genes. ConclusionsThis study provides novel insights into the molecular interplay between cellular senescence and the UC to CRC transition. The identified biomarkers not only offer strong diagnostic potential but also represent promising targets for therapeutic intervention, paving the way for improved clinical management of UC associated CRC.

bioinformatics↗

bioRxiv2025

Experimental evidence of stress-induced critical state in schooling fish

How do animal groups dynamically adjust their collective behavior in response to environmental changes is an open and challenging question. Here, we investigate the mechanisms that allow fish schools to tune their collective state under stress, testing the hypothesis that these systems operate near criticality, a state maximizing sensitivity, responsiveness, and adaptability. We combine experiments and data-driven computational modeling to study how group size and stress influence the collective behavior of rummy-nose tetras (Hemigrammus rhodostomus). We quantify the collective state of fish schools using polarization, milling, and cohesion metrics and use a burst-and-coast model to infer the social interaction parameters that drive these behaviors. Our results indicate that group size modulates stress levels, with smaller groups experiencing higher baseline stress, likely due to a reduced social buffering effect. Under stress, fish adjust the strength of their social interactions in a way that leads the group into a critical state, thus enhancing its sensitivity to perturbations and facilitating rapid adaptation. However, large groups require an external stressor to enter the critical regime, whereas small groups are already near this state. Unlike previous studies suggesting that fish adjust their interaction network structure under risk, our results suggest that the intensity of social interactions, rather than network structure, governs collective state transitions. This simpler mechanism reduces cognitive demands while enabling dynamic adaptation. By revealing how stress and group size drive self-organization toward criticality, our study provides fundamental insights into the adaptability of collective biological systems and the emergent properties in animal groups.

animal behavior and cognition↗

bioRxiv2024

Origin and stepwise improvement of vertebrate lungs

Lungs, essential for terrestrial vertebrates and present in bony fishes but absent in cartilaginous fishes, provide an ideal model for studying organ origination. Our study analyzed single-cell RNA sequencing data from mature and developing vertebrate lungs, revealing substantial similarities in cell composition, developmental trajectories and gene expression pattern across species. Notably, most lung-related genes are also present in cartilaginous fishes, indicating that gene presence alone does not guarantee lung development. We identified thousands of lung regulatory elements specific to bony fishes, with higher concentrations around genes such as tbx4 and the hoxb gene cluster. These regulatory changes might contribute to lung emergence as well as the unique co-expression patterns in lung epithelial cells, such as those related to pulmonary surfactants and cell morphology. Our research also revealed that AT1 cells are specific to mammals, and we identified a mammal-specific gene, sfta2. Knockout experiments demonstrated that sfta2 deletion causes severe respiratory defects in mice, underscoring its critical role in specialized mammalian lungs. In conclusion, our results demonstrate that the origin and evolution of lungs are driven by a complex interplay of regulatory network modifications and the emergence of new genes, underscoring the multifaceted nature of organ evolution.

evolutionary biology↗

bioRxiv2024

Tractography-based automated identification of the retinogeniculate visual pathway with novel microstructure-informed supervised contrastive learning

The retinogeniculate visual pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus. Identification and visualization of the RGVP are important in studying the anatomy of the visual system and can inform the treatment of related brain diseases. Diffusion MRI (dMRI) tractography is an advanced imaging method that uniquely enables in vivo mapping of the 3D trajectory of the RGVP. Currently, identification of the RGVP from tractography data relies on expert (manual) selection of tractography streamlines, which is time-consuming, has high clinical and expert labor costs, and is affected by inter-observer variability. In this paper, we present a novel deep learning framework, DeepRGVP, to enable fast and accurate identification of the RGVP from dMRI tractography data. We design a novel microstructure-informed supervised contrastive learning method that leverages both streamline label and tissue microstructure information to determine positive and negative pairs. We propose a simple and successful streamline-level data augmentation method to address highly imbalanced training data, where the number of RGVP streamlines is much lower than that of non-RGVP streamlines. We perform comparisons with several state-of-the-art deep learning methods that were designed for tractography parcellation, and we show superior RGVP identification results using DeepRGVP. In addition, we demonstrate a good generalizability of DeepRGVP to dMRI tractography data from neurosurgical patients with pituitary tumors and we show DeepRGVP can successfully identify RGVPs despite the effect of lesions affecting the RGVPs. Overall, our study shows the high potential of using deep learning to automatically identify the RGVP.

neuroscience↗

bioRxiv2023

A semi-automated cell tracking protocol for quantitative analyses of neutrophil swarming to sterile and S. aureus contaminated bone implants in a mouse femur model

Implant-associated osteomyelitis remains a major orthopaedic problem. As neutrophil swarming to the surgical site is a critical host response to prevent infection, visualization and quantification of this dynamic behavior at the native microenvironment of infection will elucidate previously unrecognized mechanisms central to understanding the host response. We recently developed longitudinal intravital imaging of the bone marrow (LIMB) to visualize fluorescent S. aureus on a contaminated transfemoral implant and host cells in live mice, which allows for direct visualization of bacteria colonization of the implant and host cellular responses using two-photon laser scanning microscopy. To the end of rigorous and reproducible quantitative outcomes of neutrophil swarming kinetics in this model, we developed a protocol for robust segmentation, tracking, and quantifications of neutrophil dynamics adapted from Trainable Weka Segmentation and TrackMate, two readily available Fiji/ImageJ plugins. In this work, Catchup mice with tdTomato expressing neutrophils received a transfemoral pin with or without ECFP-expressing USA300 methicillin-resistant Staphylococcus aureus (MRSA) to obtain 30-minute LIMB videos at 2-, 4-, and 6-hours post-implantation. The developed semi-automated neutrophil tracking protocol was executed independently by two users to quantify the distance, displacement, speed, velocity, and directionality of the target cells. The results revealed high inter-reader reliability for all outcomes (ICC > 0.98; p > 0.05). Consistent with the established paradigm on increased neutrophil swarming during active infection, the results also demonstrated increased neutrophil speed and velocity at all measured time points, and increased displacement at later time points (6 hours) in infected versus uninfected mice (p < 0.05). Neutrophils and bacteria also exhibit directionality during migration in the infected mice. The semi-automated cell tracking protocol provides a streamlined approach to robustly identify and track individual cells across diverse experimental settings and eliminates inter-observer variability.

immunology↗

bioRxiv2023

Implantable nanophotonic neural probes for integrated patterned photostimulation and electrophysiology recording

Optogenetics has transformed neuroscience by allowing precise manipulation of neural circuits with light [1-5]. However, a central difficulty has been to deliver spatially shaped light and record deep within the brain without causing damage or significant heating. Current approaches form the light beam in free space and record the neural activity using fluorescence imaging or separately inserted electrodes [6-9], but attenuation limits optical penetration to around 1 mm of the brain surface [10]. Here, we overcome this challenge with foundry-fabricated implantable silicon neural probes that combine microelectrodes for electrophysiology recordings with nanophotonic circuits that emit light with engineered beam profiles and minimal thermal impact. Our experiments reveal that planar light sheets, emitted by our neural probes, excited more neurons and induced greater firing rate fatigue in layers V and VI of the motor and somatosensory cortex of Thy1-ChR2 mice at lower output intensities than low divergence beams. In the hippocampus of an epilepsy mouse model, we induced seizures, a network-wide response, with light sheets without exceeding the[~] 1{whitebullet}C limit for thermally induced electrophysiological responses [11-13]. These findings show that optical spatial profiles can be tailored for optogenetic stimulation paradigms and that the probes can photostimulate and record neural activity at single or population levels while minimizing thermal damage to brain tissue. The neural probes, made in a commercial silicon photonics foundry on 200-mm silicon wafers, demonstrate the manufacturability of the technology. The prospect of monolithically integrating additional well-established silicon photonics devices, such as wavelength and polarization multiplexers, temperature sensors, and optical power monitors, into the probes holds the potential of realizing more versatile, implantable tools for multimodal brain activity mapping.

bioengineering↗

bioRxiv2023

Decapitated body intelligence (DBI) in cricket Gryllodes sigillatus

Backgroundintelligence is a highly complex problem. The decapitated insect exhibits various behaviors, indicating that they may have intelligence. Recent studies have reported organoid intelligence (OI) that lab-grown organoids also possess intelligence. This study investigated the response of decapitated crickets to different chemical stimuli to determine whether decapitated crickets have intelligence. MethodsWe used deionized water, NaCl, sucrose, and sodium hypochlorite to stimulate the front legs of the decapitated crickets and lesion the T1-T2 nerve connection of the thoracic ganglia. The behavioral response types of their forelegs were recorded. Reaction time, incidence rate, and total number of responses were calculated and analyzed. ResultsThe decapitated crickets exhibit four types of responses: leg extension, leg withdrawal, leg lift, and jump. The reaction time and incidence rate varied depending on the type and concentration of the stimulant solution. The total number of responses gradually increased with deionized water, NaCl, sucrose, and sodium hypochlorite. The lesion experiments further revealed that the only T1 thoracic ganglion can control stimulating behavior. ConclusionThe decapitated crickets possess the intelligence of perceiving stimuli and taking corresponding action. We called it decapitated body intelligence (DBI) or extrabrain intelligence (EI), which suggests that intelligence is not localized exclusively in the brain but also resides in insect ganglia. This finding opens up new ideas and avenues for the study of intelligence and the brain.

neuroscience↗

bioRxiv2023

Tuning social interactions' strength drives collective response to light intensity in schooling fish

Schooling fish heavily rely on visual cues to interact with neighbors and avoid obstacles. The availability of sensory information is influenced by environmental conditions and changes in the physical environment that can alter the sensory environment of the fish, which in turn affects individual and group movements. In this study, we combine experiments and data-driven modeling to investigate the impact of varying levels of light intensity on social interactions and collective behavior in rummy-nose tetra fish. The trajectories of single fish and groups of fish swimming in a tank under different lighting conditions were analyzed to quantify their movements and spatial distribution. Interaction functions between two individuals and the fish interaction with the tank wall were reconstructed and modeled for each light condition. Our results demonstrate that light intensity strongly modulates social interactions between fish and their reactions to obstacles, which then impact collective motion patterns that emerge at the group level.

animal behavior and cognition↗

bioRxiv2023

Amorphous calcium phosphate-coated surfaces as a model for bone microenvironment in prostate cancer

Bone metastasis remains one of the biggest challenges in the treatment of prostate cancer, and other solid tumors such as breast, lung, and colon. Modeling a complex microenvironment in-vitro, such as the bone niche, requires interrogation of cell-cell interactions, specific extracellular matrix proteins and a high calcium environment. Here, we present a fast and cost-effective system in which commercially available, non-adhesive, cell culture vessels are coated with amorphous calcium phosphate (ACP) as a surrogate for bone matrix. We further present modified protocols for subculturing cells, as well as nucleic acid and protein collection in high calcium samples. We find that prostate epithelial cell lines show increased adhesion and proliferation when cultured in these surfaces, as well as independence from androgen starvation. We observe gene expression changes on ACP surfaces in early adenocarcinoma cell lines which may reflect alterations relevant to prostate cancer progression. Summary statementTo model the role of calcium in the microenvironment of the metastatic bone niche, we developed a cost-effective way to coat cell culture vessels in bioavailable calcium, and show that it has an effect on prostate cancer cell survival

cancer biology↗