Biology subjects

Edwards, J.

Publications and source records attributed to Edwards, J..

At least 19 recordsLinked to original sources

bioRxiv2026

A breeder in the sky: scoring flowering with fewer flights

Flowering time is a trait of broad interest and importance to both plant breeders and plant biologists. Unlike many other traits, flowering time cannot be scored accurately from a single observation; its measurement requires repeated observations of the same experiments over time. Both classification- and object-detection-based approaches have demonstrated the potential to estimate flowering time from Unmanned aerial vehicle (UAV) imagery rather than by manual observation, but they still require data collection at many time points. Here, we train and deploy a regression-based framework for scoring flowering time. Using a dataset of more than 200,000 UAV images and associated flowering-time records collected across 27 environments, we demonstrate that this approach enables the prediction of flowering time from as few as one observation per field experiment and successfully generalizes to field experiments in environments not represented in the training dataset. These results indicate that regression-based approaches for predicting flowering time from sparse UAV observations have the potential to substantially reduce the data-collection burden in field experiments

plant biology↗

bioRxiv2026

An open field phenomics resource for multimodal maize yield prediction across divergent environments

Temporal drone phenotyping captures crop development, but irregular flight schedules complicate comparisons across environments. We release curated imagery from 356 flights across 19 Genomes to Fields environments containing 1,180 maize (Zea mays L.) hybrids. To evaluate its utility, we integrated functional principal components of vegetation index and weather trajectories with genomic information. Combinined genomic and phenomic kernels improved yield prediction, reaching correlations up to r = 0.501 for held-out hybrids in environments represented in training and 0.408 when environments were also withheld. Accumulated growing degree days offered no consistent predictive advantage over days after planting, and weather contributed modest, task-dependent gains. A transformer neural process learned directly from irregular observations, serving as a novel application of neural process models in agriculture. Mapping vegetation index functional principal components identified recurrent quantitative trait loci on chromosomes 3 and 7. This resource and its reproducible analyses guide the use of temporal spectral data for crop prediction and genetic discovery.

plant biology↗

bioRxiv2026

Glandular architecture and malignant behaviour in colorectal cancer is regulated by the sialomucin Podocalyxin.

Glandular architecture-the coordination of lumen-containing structures by an apical-basal polarised epithelium-is frequently maintained in colorectal cancer (CRC), yet whether it actively contributes to tumour progression or metastatic competence remains unclear. Here, we identify Podocalyxin (PODXL), a developmental regulator of epithelial lumen formation, as a key determinant of glandular tumour architecture in CRC. PODXL is upregulated in CRC, particularly in poor-prognosis Consensus Molecular Subtype 4 (CMS4) tumours, where high expression predicts reduced survival. Using genetically engineered mouse models, matched organoids, human cell lines and xenografts, we show that PODXL promotes organisation of CRC cells into gland-like, lumen-containing structures. Loss of PODXL disrupts glandular architecture in both primary tumours and liver metastases, reducing tumour growth and metastatic colonisation. Mechanistically, TGF-{beta} signalling drives PODXL upregulation. Together, these findings establish glandular architecture as an active determinant of CRC progression and identify PODXL as a functional contributor rather than merely a prognostic biomarker.

cancer biology↗

bioRxiv2026

Crop-specific agricultural land use and Rift Valley fever outbreaks in Uganda: a longitudinal compositional analysis

Rift Valley fever (RVF) is a mosquito-borne disease that can cause severe illness and death in both humans and livestock. Since 2016, Uganda has experienced recurrent but localized RVF outbreaks concentrated in the countrys southwestern region. The ecological drivers of this emergence remain unclear, as outbreaks have occurred throughout the year and show little association with meteorological patterns. We evaluated whether crop cultivation, particularly banana cultivation, is associated with RVF outbreak occurrence after controlling for likely confounders. We conducted a longitudinal study of human-inhabited 5 x 5 km grid cells across southwestern Uganda from 2016-2024. Annual Sentinel-2 satellite imagery composites were used to classify land cover into banana, coffee, ground crops, and non-crop categories, and the proportion of each land type was calculated for every grid-cell year. Because land cover proportions are compositional, isometric log-ratio transformations were used to estimate the independent effects of each land type. Confounding was addressed through propensity weighting, and crop substitution effects were estimated using g-computation. Banana land cover was the only land type consistently associated with increased RVF outbreak likelihood. In grid-cell years with low baseline banana cover, a 10-percentage point substitution from other land classes into banana was associated with a 1.64-fold increase in the odds of an RVF outbreak (95% CI: 1.17-2.29). In a simplified banana-only model, each 10-percentage point increase in banana cover was associated with a 1.21-fold increase in outbreak odds (95% CI: 1.02-1.43). Holding banana cover constant, substitutions among coffee, ground crop, and non-crop land showed weak or null associations. These findings suggest that banana cultivation may be an important ecological feature influencing RVF transmission dynamics and outbreak risk in southwestern Uganda. Author SummaryRift Valley fever (RVF) is a mosquito-borne disease that affects both humans and livestock and has caused repeated outbreaks in southwestern Uganda since 2016. While rainfall and flooding are often linked to RVF outbreaks elsewhere, Ugandas recent outbreaks have occurred across seasons and are not well explained by weather patterns alone. We investigated whether agricultural land use could help explain where outbreaks occur. Using satellite imagery from 2016-2024, we measured the amount of banana cultivation, coffee cultivation, ground crops, and non-crop land across southwestern Uganda and evaluated their association with RVF outbreak occurrence. We found that areas with greater banana cultivation were consistently more likely to experience RVF outbreaks, even after accounting for environmental and demographic factors. In contrast, coffee, ground crops, and non-crop land showed little evidence of an independent association with outbreak risk. These findings suggest that banana cultivation may create ecological conditions that favor RVF transmission. Rather than indicating that bananas themselves cause disease, the results point to banana-growing landscapes as potential environments where interactions among mosquitoes, livestock, and humans may increase transmission opportunities. Understanding these local ecological drivers could help improve surveillance, risk assessment, and prevention strategies for RVF in Uganda and other endemic regions.

ecology↗

bioRxiv2026

Niche constraints drive differences between mycorrhizal fungal guilds in future range shifts

Mycorrhizal fungi are a diverse and ubiquitous group of plant symbionts whose distribution strongly influences ecosystem function across the globe. Yet, until now, we do not have quantitative data on the range sizes of different mycorrhizal fungal taxa, limiting our capacity to forecast future shifts in community composition and function. Here, we use 115,924 DNA sequence-derived observations to map the distribution of 651 common mycorrhizal fungal taxa and forecast future changes to their range sizes. We demonstrate that climate, plant cover, and soil factors, particularly mean annual temperature, net primary productivity, and soil organic carbon, exert major control over mycorrhizal fungal distributions. Based on these drivers, the ecological niches of mycorrhizal fungi consistently differ between arbuscular and ectomycorrhizal functional guilds. Arbuscular mycorrhizal fungal taxa generally occupy a wider niche breadth than ectomycorrhizal fungi, occurring across larger ranges of climate, soil, plant cover, topography, and disturbance conditions. Our models also predict widespread decreases in the suitable range size of mycorrhizal fungal taxa under projected future global climates, with average ranges decreasing by 13.8% or ~2.2 million km2 under high emissions scenarios (ssp5-8.5). This decrease in projected range size will be most pronounced for ectomycorrhizal fungi, strongly linked to constraints from their smaller overall niches. By generating a global atlas of common mycorrhizal fungi and their associated environmental niche, we establish a critical baseline for widely suspected declines in global fungal biodiversity.

ecology↗

bioRxiv2026

Unique nasal cell states induced by common pediatric respiratory viruses

Respiratory viral infections in early childhood are major drivers of acute morbidity and long-term airway disease, yet how distinct viruses remodel the pediatric nasal mucosa at cellular resolution remains unresolved. Here, we generated a single-cell RNA sequencing atlas of 335,174 nasal epithelial and immune cells from 132 children under five years of age with SARS-CoV-2, rhinovirus, or respiratory syncytial virus (RSV) infection, alongside uninfected controls. Mapping viral transcripts to individual cells revealed virus-specific infected epithelial states: an NF-kB-responsive ciliated subset in SARS-CoV-2 and a previously undescribed KRT17+ squamous-like subset in RSV. We delineated divergent mucosal response programs, including a robust interferon (IFN) response in SARS-CoV-2, an IL-13-responsive secretory program in rhinovirus, and heightened inflammatory and cytotoxic immune activation in RSV. In RSV, specific immune subsets and elevated IFN-response signatures were associated with disease severity, whereas rhinovirus-induced wheeze was marked by expansion of a CST1+ goblet cell subset. Integration of asthma genome-wide association data with our atlas revealed a KRT13+ hillock-like squamous epithelial subset enriched for expression of childhood-onset asthma risk loci. Finally, we demonstrate that this resource enables high-resolution annotation of independent pediatric cohorts in Kolkata, India and rural Bangladesh. Together, this atlas establishes a comprehensive view of antiviral immunity in the pediatric nasal mucosa and defines virus-specific mucosal immune programs relevant to disease severity and asthma risk in early life.

immunology↗

bioRxiv2026

Dissecting genetic variance structure and evaluating genomic prediction models for single-cross hybrids derived from Stiff Stalk and Non-Stiff Stalk maize heterotic groups

The early 20th-century discovery of heterosis and the establishment of heterotic groups transformed maize (Zea mays L.) into a keystone of global agriculture. However, maize breeding faces two significant challenges: the gradual decline of general combining ability (GCA) variance within heterotic groups and the impracticality of testing all possible single crosses in the early stages of a breeding program. Here, we developed genomic best linear unbiased prediction (GBLUP)-based multi-kernel models, using additive and two alternative non-additive genomic relationship matrices, to estimate the variance components associated with the GCA of Stiff Stalk (SS) and Non-Stiff Stalk (NSS) heterotic groups and the specific combining ability (SCA) arising from their crosses. We further applied these models to predict the performance of untested single-cross combinations under varying levels of parental information. We showed that the SS and NSS groups retained significant GCA variance across traits in both early- and late-maturity groups. The SS group, in contrast, exhibited no detectable GCA variance in grain yield for the intermediate-flowering subset of hybrids, highlighting a limitation for future genetic improvement. Furthermore, our results showed that GBLUP-based multi-kernel models effectively identified superior hybrids when parental information was available. In the absence of this information, however, these models underperformed compared to covariance-based approaches. Both types of non-additive matrices produced similar results, affirming the robustness of the inferred genetic architecture. Overall, this study sheds light on the future use of US maize commercial germplasm and demonstrates how GBLUP-based multi-kernel models can improve the efficiency of hybrid breeding programs.

genetics↗

bioRxiv2026

Zinc excess promotes lysosome remodeling by activating HLH-30/TFEB through the action of the high zinc sensor HIZR-1.

Zinc is an essential element that plays many roles in animals. Since excess zinc is toxic, animals have evolved sophisticated mechanisms to achieve homeostasis. A conserved mechanism is to store excess zinc in specialized lysosomes, which contributes to zinc detoxification and provides a supply when zinc becomes limiting. In C. elegans excess zinc conditions promote an increase in lysosome-related organelles called bilobed granules. Defining how zinc-regulated transcription drives the observed lysosome remodeling is key to understanding zinc homeostasis processes. Here we describe a positively regulated zinc cascade controlled by hizr-1 and hlh-30/TFEB, which encode the C. elegans high zinc sensor and the master regulator of the autophagy-lysosomal pathway, respectively; essential for connecting excess zinc homeostasis to lysosome biogenesis and remodeling. Our transcriptomic, genetic, and bioinformatic studies indicate that hizr-1 and hlh-30 are necessary and sufficient to activate transcription of lysosome genes under excess zinc conditions. In our regulatory model, zinc binding activates HIZR-1 protein, which accumulates in the nucleus and activates genes containing the HZA enhancer, including hlh-30. HLH-30 protein accumulates in the nucleus and activates genes containing the E-box enhancer. Genetic analysis of loss-of-function mutants demonstrated that both hizr-1 and hlh-30 are necessary for animals to tolerate excess zinc. Furthermore, HLH-30 promotes the increase in the number of acidified compartments, whereas HIZR-1 promotes the increase in the volume of the expansion compartment. These results define a genetic pathway that responds to excess zinc by increasing the number of lysosome-related organelles and their capacity to store and detoxify cytosolic zinc.

genetics↗

bioRxiv2026

Collagen IV of basement membrane: V. Bromide-mediated sulfilimine bonds interlock the quaternary structure of NC1-hexamer of scaffolds enabling metazoan evolution.

Collagen-IV (Col-IV) scaffolds, a primordial basement membrane component, enabled animal multicellularity, evolution and adaptation. These scaffolds provide tensile strength and tether macromolecules, forming supramolecular complexes that interact with cell-surface receptors and influence cell-behavior. Triple-helical Col-IV protomers, composed of three -chains, with a trimeric globular NC1-domain at the C-terminus, oligomerize forming a NC1-hexamer structure that connects adjoining protomers of Col-IV121, Col-IV556--121, and Col-IV345 scaffolds. Hexamer formation and stability are driven by the extracellular chloride concentration-"chloride pressure". Hexamer structure is reinforced by six sulfilimine bonds forming covalent crosslinks that weld together trimeric NC1-domains of adjoining protomers. We recently found evidence that sulfilimine bonds, independent of chloride, stabilize the quaternary structure of the Col-IV345 hexamer of the Col-IV345 scaffold. Here, we sought to determine whether this function also pertains to the Col-IV121 scaffold that occurs ubiquitously across the animal kingdom, and whether bromine, a cofactor of peroxidasin in bond formation, are evolutionary conserved. We found that sulfilimine bonds stabilized the quaternary structure of the Col-IV121 hexamer of bovine, mouse and a basal cnidarian, Nematostella vectensis, and that the mechanism of bond formation mediated by peroxidasin and bromide is evolutionary conserved. Analyses of the crystal structure of the NC1-hexamer revealed that sulfilimine bonds covalently fasten a clasp-motif across the trimer-trimer interface, interlocking the domain-swapping region of neighboring subunits, which reinforces the hexamer quaternary structure imposed by chloride conformational constraints. Collectively, our findings reveal that the sulfilimine-bond reinforcement is a critical event in Col-IV scaffold assembly enabling multicellularity, evolution and adaptation of metazoans, beginning with ancient cnidarians.

molecular biology↗

bioRxiv2026

Novel repressors of cambium activity in Arabidopsis

Wood is the greatest reservoir of terrestrial biomass and an essential carbon sink. Formed of xylem, it is derived from the cambium, a meristematic zone within plant stems from which phloem also forms. In Arabidopsis, cell division within the cambium is promoted by three major factors: auxin, cytokinin, and the TDIF-PXY ligand-receptor pair. Meristems and other stem cell populations are typically regulated by a balance between cell division-promoting factors and those that repress cell division to control meristem size, however few factors with cambium-repressing activity are known. Here we combined transcriptomics and transcriptional network analysis, which led to identification of related homeodomain zinc-finger transcription factors, ATHB23, ATHB30, and ATHB34, that repress cambium activity. These factors inhibit cambium activity by directly binding of promoters from a subset of auxin, cytokinin and TDIF-PXY transcriptional target genes, resulting in attenuation of their transcription. Our findings thus reveal a new mechanism underpinning balanced cambium activity.

plant biology↗

bioRxiv2025

Gene-by-Environment Interaction Significantly Drives Bacterial Endophyte Communities in Maize Stalks

1.BackgroundMany microbes are known to boost the performance of crop plants, and their use as crop treatments ("biologicals") is an active area of research and commercialization. Although many identified microbes can boost plant production under laboratory settings, most fail to translate to field settings, and even the ones that are commercialized are often unreliable. While many factors likely underlie these issues, one that has been underexplored is the idea that interactions between plants and microbes can vary across both different host genetics and different environments, and that specific combinations of host and environment can result in very different microbial outcomes. ResultsTo quantify how a plant microbiome can change across host genotype and environment and to determine the relative importance of these factors, we sampled maize stalks from 20 specific hybrid varieties grown at 15 locations in the United States. Using 16S rRNA gene sequencing, we find that the stalk microbiome is highly variable, with a handful of bacterial taxa conserved at broader taxonomic levels (Phylum, Class) and almost none at finer levels (Genus, Species). Local environment and gene-by-environment interactions both had consistently large and significant effects on the microbial community (measured by alpha-and beta-diversity summary statistics, individual taxa, and inferred functional capacity), whereas host genotype had little to no consistent effect across environments. We also identified specific soil factors (pH and potassium) as the most significant environmental drivers of the community, even though these communities were living inside the stalks. ConclusionsTaken together, our results indicate that while host genetics can significantly affect the stalk microbial community, these effects are almost entirely predicated on interactions with the environment. These results imply that reliable deployment of microbes for crop production will require significant investment in trials across many locations and genetic backgrounds, either to estimate the GxE effects directly or to screen for microbes whose effects are less dependent on these two factors.

microbiology↗

bioRxiv2025

Self-Supervised AI Reveals a Hidden Landscape of Prognostic Spatial Patterns in Multiplex Immunofluorescence Images

Modern spatial proteomic methods, such as multiplex immunofluorescence (mIF) imaging, offer a data-rich view of spatial biology in intact tissues. However, interpreting its complexity is a major bottleneck, limiting its potential for biological discovery and clinical translation. Current computational methods often rely on segmentation-based approaches that discard crucial morphological information and are limited to testing pre-defined hypotheses. Here, we introduce a self-supervised learning (SSL) framework that enables hypothesis-agnostic, context-aware discovery of biomarkers directly from mIF images. Our approach extracts rich feature representations that capture holistic architectural patterns, which integrate cellular morphology, marker interactions, and microenvironmental context without human supervision. Applying this framework to over 7,000 mIF tissue images from over 1,800 patients in two distinct cancer types, we demonstrate superior prognostic performance over conventional segmentation analyses. The method autonomously identified previously unknown and potentially clinically actionable biological patterns. In lung adenocarcinoma, these include a Ki67-mediated immune evasion phenotype, a sub-cellular pattern of GLB1 expression which aligns with low-grade EGFR-driven tumours, and distinct modes of tumour-immune interaction in PD-L1+ patients. We also find a regulatory T-cell-mediated immunosupressive environment promoting tumour budding in colorectal carcinoma. Our work establishes SSL as a powerful, scalable, and unbiased platform to decode tissue ecosystems while being fully explainable without pre-defined hypotheses. This paradigm shift transforms high-plex imaging from a hypothesistesting tool into a hypothesis-generating engine that can accelerate the discovery of next-generation spatial biomarkers.

cancer biology↗

bioRxiv2025

Distributional Data Analysis Uncovers Hundreds of Novel and Heritable Phenomic Features from Temporal Cotton and Maize Drone Imagery

Genomic and phenomic analyses suggest additional heritable phenomic features can improve modeling of important end traits like senescence or yield. Field phenotyping generally uses trait values averaged across individual experimental units (plants or numerous plants within plots), ignoring the full distributional pattern of collected measures. Images of plants or plots, as captured by drones (unoccupied aerial vehicles / UAVs / drones), can be viewed as individual distribution functions that capture biological information. This study introduces and validates distributional data analysis in two crops and experiment types - cotton (Gossypium hirsutum L.) single plant vegetation index (VI) analysis and maize (Zea mays L.) plot-level yield predictions. In both crops, the concept of within-day variance decomposition was demonstrated. In cotton, genotypes exerted significant influences on temporal quantile functions of VIs. Maize yield prediction using distributional data with elastic-net regression indicated improvements in yield prediction between 12.7%-21.6% with quantiles outside the conventionally used median responsible for added predictive power. A novel data visualization method for per-pixel heritability allowed distributional features to be explainable and interpretable. These results have implications for future plant phenomic studies, indicating that distributional data analysis applied across temporal imagery captures novel, heritable, and interpretable biological signal that is lost when working with conventional measures of central tendency such as mean or median summary values of experimental units. SignificanceRepeated aerial imaging of agricultural experiments produces image data sets that capture plant development in high spatial and temporal resolutions. Frequently, images are summarized by measures of central tendency, such as mean or median values. Here, functional data distributional methods were applied to cotton (Gossypium hirsutum L.) and maize (Zea mays L.) image data, capturing more information than standard approaches. Cotton genotypes significantly impacted distributional spectral data while in maize, distributional data enabled more accurate predictions of grain yield versus models trained with median data alone. Distributional data were more explainable by genetics, with novel data visualization techniques able to shine light on specific parts of plant imagery with high and low genetic variance.

plant biology↗

bioRxiv2025

VEGF-A/C co-stimulation, without shear stress, triggers the polarization of lymphatic microvessels

The lymphatic system maintains interstitial fluid homeostasis and supports immune function through dynamic regulation of its architecture mediated by molecular signals--such as vascular endothelial growth factors (VEGFs)--and physical cues. While VEGFs are known to promote endothelial proliferation, their broader roles in tissue organization remain under investigation. Using a lymphatic vessel-on-a-chip platform, we examine how lymphatic endothelial cells (LECs) respond to VEGF-A, VEGF-C, or their combination. We find that co-stimulation synergistically enhances lymphangiogenic sprouting while preserving barrier integrity. Co-stimulation also induces axial polarization of the tissue along the vessel axis, even in the absence of external mechanical stimuli. This polarization requires activation of the VEGFR2/VEGFR3 heterodimer and is disrupted by inhibition of the Src-dependent mechanotransduction pathway. Further co-stimulation enhances LEC motility and triggers vessel contraction. Modeling suggests that the tubular geometry of the lymphatic monolayer imposes intrinsic mechanical anisotropy--softer in the circumferential than axial direction. This geometrically-encoded stiffness landscape directs cell migration along the stiffer axis, uncovering a form of durotaxis driven by curvature-induced anisotropy. These results highlight a previously unrecognized mechanism by which biochemical and biophysical cues direct lymphatic tissue polarization, offering new insight into how geometry and mechanosensing shape lymphatic function.

bioengineering↗

bioRxiv2025

Acute induction of IFNα is responsible for the attenuation of the live measles vaccine

The live-attenuated measles vaccine (LAMV) protects against measles in a safe, efficacious and durable manner. However, the mechanism by which LAMV is attenuated is not well understood, contributing to the increased vaccine hesitancy that has caused a worldwide resurgence of measles. Here, we provide a molecular model of attenuation that implicates increased host innate immune responses and increased LAMV susceptibility to those responses. Our study leverages both in vitro and in vivo models of infection to find that acute induction of innate immunity in immune cells is the critical determinant of LAMV attenuation. We show that LAMV, in contrast to pathogenic wild type measles virus (MeV), causes a strong IFN response in primary human peripheral blood mononuclear cells, which restricts viral replication and spread in a post-entry manner. LAMV can enter, transcribe viral mRNA and translate viral proteins in immune cells, but is not able to form infectious particles and spread from cell to cell. Specifically, we find that mutations conserved across LAMV strains in the P/V/C and H genes are responsible for the induction of IFN and the restriction of infectious virus production. In PBMC cultures and in rhesus macaques, LAMV infection also results in the acute induction of proinflammatory cytokines that likely play a role in the immunogenicity of the vaccine. Overall, our study provides a virological and immunological framework for LAMV attenuation which can be leveraged in repurposing the LAMV backbone and in future vaccine design.

microbiology↗

bioRxiv2025

The characteristic of epithelial-specific phenotypes and immunosuppressive microenvironment in the context of tumour budding in colorectal cancer

BackgroundTumour budding (TB), defined as a small cluster of up to four cells at the invasive front of the tumour, is a well-established independent and robust prognostic biomarker in colorectal cancer (CRC). This is strongly associated with adverse clinicopathological features and poor survival outcomes. Despite its clinical relevance, the precise underlying mechanism responsible for TB phenomenon remains unclear. MethodsMulti-omic approaches from bulk, regional GeoMx and Spatial Molecular Imager (SMI) RNA were used to identify the underlying mechanism of TB and its possible correlation with tumour microenvironment (TME) in CRC tissue. The results were validated using immunohistochemistry (IHC) and multiplex immunofluorescence (mIF) staining. ResultsPatients with high TB experience worse outcomes and associate with adverse clinical factors across two independent CRC cohorts. Bulk and regional RNA expression analyses reveal that tumours with high TB are significantly enriched for TNF- and TGF-{beta} signatures in both cohorts. Single cell CosMx SMI analysis confirmed TB cells exhibit higher expression of these signatures than adjacent invasive edge tumour cells. Elevated cyclinD1 expression was also observed within TB, and high cyclinD1 levels tend to experience poorer CRC prognosis. Furthermore, regional bulk RNA expression within the non-tumour (PanCK-) invasive edge areas demonstrated that tumours exhibiting high TB revealed the significantly differential expressions of immune-related genes (e.g. CD3, NKG7, IL6, CXCR6, CD47, IFNAR1 and VSIR). Single cell CosMx SMI analysis revealed that cancer-associated fibroblasts (CAFs) were physically the closest cells to TB cells. This spatial proximity was confirmed at the protein level using mIF, where the distance from TB to CD68+ macrophages predicted significantly poorer CRC outcomes. ConclusionThis multi-omic study confirms the prognostic significance of TB in CRC patients across two independent cohorts. Our findings highlight that TNF- and TGF-{beta} signalling play a crucial role in budding cells development by regulating cyclinD1. Furthermore, the transcriptomic analysis reveals an immunosuppressive niche characterised by reduced immune activity and close spatial interactions with CAFs and macrophages Ultimately, this study provides valuable insight into TBs underlying mechanism and its complex interactions within the TME. This could provide a foundation for developing targeted therapeutic strategies in CRC.

cancer biology↗

bioRxiv2025

Dose-dependent changes in global brain activity and functional connectivity following exposure to psilocybin: a BOLD MRI study in awake rats.

Psilocybin is a hallucinogen with complex neurobiological and behavioral effects. This is the first study to use MRI to follow functional changes in brain activity in response to different doses of psilocybin in fully awake, drug naive rats. Female and male rats were given IP injections of vehicle or psilocybin in doses of 0.03 mg/kg, 0.3 mg/kg, and 3.0 mg/kg while fully awake during the imaging session. Changes in BOLD signal were recorded over a 20 min window. Data for resting state functional connectivity were collected approximately 35 min post injection All data were registered to rat 3D MRI atlas with 173 brain regions providing site-specific changes in global brain activity and changes in functional connectivity. Treatment with psilocybin resulted in a significant dose-dependent increase in positive BOLD signal. The areas most affected by the acute presentation of psilocybin were the somatosensory cortex, basal ganglia and thalamus. Females were significantly more sensitive to the 0.3 mg/kg dose of psilocybin than males. There was a significant dose-dependent global increase in functional connectivity, highlighted by hyperconnectivity to the cerebellum. Brain areas hypothesized to be involved in loss of sensory filtering and organization of sensory motor stimuli such as the claustrum and the cortico-basal ganglia-thalamic-cortical loop were all affected by psilocybin in a dose-dependent manner. Indeed, the general neuroanatomical circuitry associated with the psychedelic experience was affected but the direction of the BOLD signal and pattern of activity between neural networks was inconsistent with the human literature.

neuroscience↗

bioRxiv2025

Warming disrupts plant-fungal endophyte symbiosis more strongly in leaves than roots

Disruptions to species interactions from global change will negatively impact plant primary production, with broader consequences for species abundances, distribution, and community composition. Fungal endophytes that live inside plant leaves and roots could potentially mitigate plant heat stress from global warming. Conversely, disruptions of these symbioses could exacerbate the negative impacts of warming. To better understand the consistency and strength of warming-induced changes to fungal endophytes, we examined fungal leaf and root endophytes in three grassland warming experiments in the US ranging from 2 to 25 years and spanning 2000 km, 12 {degrees}C of mean annual temperature, and 600 mm of precipitation. We found that experimental warming disrupted symbiosis between plants and fungal endophytes. Colonization of plant tissues by septate fungi decreased in response to warming by 90% in plant leaves and 35% in roots. Warming also reduced fungal diversity and changed community composition in plant leaves but not roots. The strength, but not direction, of warming effects on fungal endophytes varied by up to 75% among warming experiments. Finally, warming decoupled fungal endophytes from host metabolism. Overall, warming-driven disruption of fungal endophyte community structure and function suggests that this symbiosis may not be a reliable mechanism to promote plant resilience and ameliorate stress responses under global change.

ecology↗