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At least 19 recordsLinked to original sources
PubMed2026

PASTA: versatile tyramide-oligonucleotide amplification for multimodal spatial biology.

Spatial proteomics is limited by detection sensitivity, multiplexing and multimodal integration, leaving a gap between discovery and clinical assays. Here we present protein and nucleic acid serial tyramide amplification (PASTA), using horseradish peroxidase-mediated oligonucleotide deposition and cyclical imaging for high-plex, multimodal spatial profiling. Compatible with conjugated antibodies and in situ hybridization, PASTA enables simultaneous protein and RNA codetection from formalin-fixed, paraffin-embedded samples, providing a cost-effective bridge from discovery to clinical validation.

Tyramine↗
PubMed2005

Towards biologically conformal radiation therapy (BCRT): selective IMRT dose escalation under the guidance of spatial biology distribution.

It is well known that the spatial biology distribution (e.g., clonogen density, radiosensitivity, tumor proliferation rate, functional importance) in most tumors and sensitive structures is heterogeneous. Recent progress in biological imaging is making the mapping of this distribution increasingly possible. The purpose of this work is to establish a theoretical framework to quantitatively incorporate the spatial biology data into intensity modulated radiation therapy (IMRT) inverse planning. In order to implement this, we first derive a general formula for determining the desired dose to each tumor voxel for a known biology distribution of the tumor based on a linear-quadratic model. The desired target dose distribution is then used as the prescription for inverse planning. An objective function with the voxel-dependent prescription is constructed with incorporation of the nonuniform dose prescription. The functional unit density distribution in a sensitive structure is also considered phenomenologically when constructing the objective function. Two cases with different hypothetical biology distributions are used to illustrate the new inverse planning formalism. For comparison, treatments with a few uniform dose prescriptions and a simultaneous integrated boost are also planned. The biological indices, tumor control probability (TCP) and normal tissue complication probability (NTCP), are calculated for both types of plans and the superiority of the proposed technique over the conventional dose escalation scheme is demonstrated. Our calculations revealed that it is technically feasible to produce deliberately nonuniform dose distributions with consideration of biological information. Compared with the conventional dose escalation schemes, the new technique is capable of generating biologically conformal IMRT plans that significantly improve the TCP while reducing or keeping the NTCPs at their current levels. Biologically conformal radiation therapy (BCRT) incorporates patient-specific biological information and provides an outstanding opportunity for us to truly individualize radiation treatment. The proposed formalism lays a technical foundation for BCRT and allows us to maximally exploit the technical capacity of IMRT to more intelligently escalate the radiation dose.

Dose-Response Relationship, Radiation↗
PubMed2026

Spatial biology reveals altered macrophage states in immunosuppressed non-melanoma skin cancer.

Immunosuppressed patients with non-melanoma skin cancer experience worse clinical outcomes, yet the tumor immune microenvironment associated with systemic immunosuppression remains incompletely defined. Using integrated single-cell, spatial transcriptomic, multiplex immunofluorescence, and spatial epigenomic profiling across immunocompetent and immunosuppressed tumors, we found that overall immune-cell composition was largely preserved despite differences in immune-cell distribution, spatial organization, and T cell clonality. Immunosuppressed tumors demonstrated reduced intratumoral macrophage densities, decreased T cell clonal diversity, altered antigen-presenting cell and T cell spatial interactions, and distinct fibroblast- and macrophage-associated spatial niches. Multi-cohort validation across complementary spatial and single-cell platforms identified consistent alterations in innate-adaptive immune organization in immunosuppressed tumors. Together, these findings define spatial and functional remodeling of the tumor immune microenvironment under systemic immunosuppression and provide a framework for future therapeutic investigation in high-risk patients.

Humans↗
PubMed2024

Digital pathology and spatial omics in steatohepatitis: Clinical applications and discovery potentials.

Steatohepatitis with diverse etiologies is the most common histological manifestation in patients with liver disease. However, there are currently no specific histopathological features pathognomonic for metabolic dysfunction-associated steatotic liver disease, alcohol-associated liver disease, or metabolic dysfunction-associated steatotic liver disease with increased alcohol intake. Digitizing traditional pathology slides has created an emerging field of digital pathology, allowing for easier access, storage, sharing, and analysis of whole-slide images. Artificial intelligence (AI) algorithms have been developed for whole-slide images to enhance the accuracy and speed of the histological interpretation of steatohepatitis and are currently employed in biomarker development. Spatial biology is a novel field that enables investigators to map gene and protein expression within a specific region of interest on liver histological sections, examine disease heterogeneity within tissues, and understand the relationship between molecular changes and distinct tissue morphology. Here, we review the utility of digital pathology (using linear and nonlinear microscopy) augmented with AI analysis to improve the accuracy of histological interpretation. We will also discuss the spatial omics landscape with special emphasis on the strengths and limitations of established spatial transcriptomics and proteomics technologies and their application in steatohepatitis. We then highlight the power of multimodal integration of digital pathology augmented by machine learning (ML)algorithms with spatial biology. The review concludes with a discussion of the current gaps in knowledge, the limitations and premises of these tools and technologies, and the areas of future research.

Humans↗
PubMed1990

Spatial and biological characterisation of the complete quinic acid utilisation gene cluster in Aspergillus nidulans.

Heterologous probing of restriction digests of chromosomal DNA from Aspergillus nidulans with radioactively labelled probes encoding dehydroshikimate dehydratase (QA-4) and a repressor gene (QA1-S) from Neurospora crassa revealed a pattern of hybridisation inconsistent with an equivalent single copy of each gene in A. nidulans. Screening of size-selected and total genome A. nidulans DNA libraries allowed the isolation of four unique classes of sequence, two of which hybridised to the QA-4 probe, and two of which hybridised to the QA1-S probe. In each case, one of each pair of unique sequences was able to complement the equivalent mutations qutC (= QA-4) and qutR (= QA1-S) in A. nidulans, whereas the second of each pair was unable to complement the same mutation. The complementing sequences were physically mapped relative to the previously cloned A. nidulans QUT gene cluster, demonstrating that QUTR is distal and divergently transcribed from QUTA with approximately 3.6 kb between the ATG translational start codons, and that QUTC is transcribed in the same direction as QUTD on the other side of the cluster, approximately 1.65 kb downstream of the QUTD TAA translational stop signal. The physical and genetic maps of the QUT gene cluster correlate precisely. The non-complementing A. nidulans DNA sequences that hybridise to the N. crassa QA-4 (= QUTC) and QA1-S (= QUTR) fulfill many of the criteria characteristic of pseudogenes.(ABSTRACT TRUNCATED AT 250 WORDS)

Amino Acid Sequence↗
PubMed1994

Spatial and biological characteristics of between-herd transmission of Aujeszky's disease virus.

The eradication of Aujeszky's disease virus (ADV) in Pennsylvania has suffered because the modes of viral transmission between herds are unknown. Our objective was to identify the major risk factors involved in viral transmission by comparing proportions of operation type, density, quarantine level, and vaccination status of neighboring herds for infected case and uninfected control herds. Multivariate analysis demonstrated an elevated risk of infection with local increases in the proportion of finishing floors. A local increase in the proportion of ADV-quarantined herds was shown to be a significant risk factor, as was an increase in the proportion of vaccinating herds. A reduced risk of infection was found with local increases in the number of feeder pig producer operations.

Animal Husbandry↗
PubMed2026

Convergent methodologies in prosthetic joint infection research: integrating transdisciplinary approaches to understand and prevent biofilm-driven failure of orthopaedic prostheses.

Prosthetic joint infections (PJIs) remain among the most devastating complications of arthroplasty, imposing substantial clinical, economic and patient burdens. Although culture-based diagnostics underpin current clinical practice, PJIs are biofilm-driven infections shaped by taxonomic diversity, spatial organization, host responses and surface interactions, meaning conventional approaches provide only a partial and often decontextualized view of the infection process. We examine how convergent methodologies can transform PJI research by integrating approaches that have traditionally been studied in isolation, including sequencing, transcriptomics, metabolomics, advanced imaging and culture-based characterization. We discuss how whole-genome sequencing, shotgun metagenomics, transcriptomic and metabolomic approaches resolve pathogen identity, functional activity and adaptive persistence and how cross-scale imaging and spatial biology techniques reveal where microbes colonize, interact and survive across implant surfaces. We highlight emerging opportunities to unify these datasets into coherent frameworks that capture both the molecular and physical dimensions of PJIs. Integrating these complementary approaches will enable a multi-layered understanding of PJIs that link composition, function and spatial organization. Ultimately, this provides a foundation for predictive diagnostics, precision antimicrobial strategies and improved implant design and supports a shift towards more effective, mechanism-informed management of implant-associated infection.

Prosthesis-Related Infections↗
PubMed2001

Simultaneous delivery of an active protein and neutralizing antibody: creation of separated regions of biological activity.

Spatial control over the biological activity of nerve growth factor (NGF) via a novel type of controlled-release device was demonstrated in an in vitro system. Two-layer polymer matrices that simultaneously released NGF and a neutralizing antibody (anti-NGF) from opposite faces were placed in PC12 cell-populated collagen gels. Biological activity in the gels was assessed over the course of 10 days by direct observation of the cells, which extend neuronal processes in the presence of NGF in a dose-dependent manner. The concentrations of both proteins in the gels were determined by ELISA as a function of distance from the polymer matrices at various time points. A boundary in biological activity was established within a few days of the initiation of the cultures; this boundary persisted and became more pronounced throughout the duration of the experiment. ELISA analysis revealed regions of high concentration of both NGF and anti-NGF on their respective sides of the polymer matrix early in the experiment. The theoretical amount of active NGF in the gel sections was calculated on the basis of these ELISA results; the concentration of active NGF in the region adjacent to the polymer correlated with the observed degree of biological response. These experiments suggest that spatial control over the biological activity of a potent agent can be obtained by an appropriately designed controlled-release device.

Animals↗
PubMed2002

Modelling normal tissue isoeffect distribution in conformal radiotherapy of glioblastoma provides an alternative dose escalation pattern through hypofractionation without reducing the total dose.

The purpose of this study was to prove that by using conformal external beam radiotherapy (RT) normal brain structures can be protected even when applying an alternative approach of biological dose escalation: hypofractionation (HOF) without total dose reduction (TDR). Traditional 2-dimensional (2D) and conformal 3-dimensional (3D) treatment plans were prepared for 10 gliomas representing the subanatomical sites of the supratentorial brain. Isoeffect distributions were generated by the biologically effective dose (BED) formula to analyse the effect of conventionally fractionated (CF) and HOF schedules on both the spatial biological dose distribution and biological dose-volume histograms. A comparison was made between 2D-CF (2.0 Gy/day) and 3D-HOF (2.5 Gy/day) regimens, applying the same 60 Gy total doses. Integral biologically effective dose (IBED) and volumes received biologically equivalent to a dose of 54 Gy or more (V-BED54) were calculated for the lower and upper brain stem as organs of risk. The IBED values were lower with the 3D-HOF than with the 2D-CF schedule in each tumour location, means 22.7+/-17.1 and 40.4+/-16.9 in Gy, respectively (p < 0.0001). The V-BED54 values were also smaller or equal in 90% of the cases favouring the 3D-HOF scheme. The means were 2.7+/-4.8 ccm for 3D-HOF and 10.7+/-12.7 ccm for 2D-CF (p = 0.0006). Our results suggest that with conformal RT, fraction size can gradually be increased. HOF radiotherapy regimens without TDR shorten the treatment time and seem to be an alternative way of dose escalation in the treatment of glioblastoma.

Brain↗
PubMedDate not supplied

Evolution of spatial expression pattern.

How can complex patterns of gene expression evolve? Understanding the near-precise repeatability of morphology created by animal development, through the interactions between morphogens and networks of transcription factors, is one of the most difficult outstanding problems in developmental biology. Spatial patterns are created in part by interactions between transcription factors and their DNA targets. Here we simulate the evolution of such interactions to compare the success and the evolvability of simple and complex gene networks in reaching a desired spatial pattern of expression along an embryo. We find that adding more genes to a network makes only a slight difference to evolvability. Expression patterns can evolve within a few hundred mutational events, and some simulations show partial redundancy. However, there is wide variation between simulations, with both simple and complex networks being liable to reach evolutionary "dead ends" that can only be escaped by means of an advantageous combination of individually deleterious mutations.

Biological Evolution↗
PubMed2001

Fundamental clusters in spatial 2x2 games.

The notion of fundamental clusters is introduced, serving as a rule of thumb to characterize the statistical properties of the complex behaviour of cellular automata such as spatial 2 x 2 games. They represent the smallest cluster size determining the fate of the entire system. Checking simple growth criteria allows us to decide whether the cluster-individuals, e.g. some mutant family, are capable of surviving and invading a resident population. In biology, spatial 2 x 2 games have a broad spectrum of applications ranging from the evolution of cooperation and intraspecies competition to disease spread. This methodological study allows simple classifications and long-term predictions in various biological and social models to be made. For minimal neighbourhood types, we show that the intuitive candidate, a 3 x 3 cluster, turns out to be fundamental with certain weak limitations for the Moore neighbourhood but not for the Von Neumann neighbourhood. However, in the latter case, 2 x 2 clusters generally serve as reliable indicators to whether a strategy survives. Stochasticity is added to investigate the effects of varying fractions of one strategy present at initialization time and to discuss the rich dynamic properties in greater detail. Finally, we derive Liapunov exponents for the system and show that chaos reigns in a small region where the two strategies coexist in dynamical equilibrium.

Animals↗
PubMed1997

The development of marine environmental monitoring using fish diseases.

The difficulties in interpreting the biological significance of pollutants in the marine environment led to the recognition that natural indices reflecting chemical and physical changes are required. The close interaction between host, disease (including parasites) and environment indicates that change in disease patterns offers considerable potential as a natural monitoring system in this field. This problem was addressed by the Working Groups of the International Council for the Exploration of the Sea (ICES) in the early 1980s. Since then, a series of studies have provided internationally agreed recommendations on appropriate diseases to monitor, on sampling strategies and on guidelines for diagnosis, identification and data reporting. Research in Scottish waters has shown that parasites with complex life cycles and intermediate stages which are vulnerable to pollution can give a good indication of the dispersion of pollution from a point source. However, without good knowledge of the spatial, biological and temporal variations in the occurrence of fish diseases due to natural events, there are significant dangers in the interpretation of observed differences in disease as being pollution associated. As a general rule, it is probable that trends in disease differences will be of more use in environmental quality monitoring than would be differences in absolute levels of infection between different areas.

Animals↗
PubMed2026

Extracellular vesicle miR-93-5p cargo regulates glomerular endothelial cell damage in Alport syndrome.

Modulation of miRNA expression in glomerular cells is associated with renal disease. Here, we investigated the role of miR-93-5p in mitigating glomerular damage in Alport syndrome and whether the disease-modifying activity of extracellular vesicles from human amniotic fluid stem cells (hAFSC-EVs) is mediated by their miR-93-5p cargo. We identified downregulation of miR-93-5p specifically in glomerular endothelial cells in Alport syndrome along disease progression. Silencing of miR-93-5p in hAFSC-EVs changed the transcriptomic and proteomic profile, regulating EV disease-modifying activity. Compared with naive hAFSC-EVs, silenced hAFSC-EVs did not rescue glomerular endothelial function in vitro and did not restore kidney function in vivo. We established that hAFSC-EVs regulate VEGFR1 and VEGFR2 signaling by miR-93-5p cargo transfer, highlighting that miR-93-5p can restore glomerular endothelial cell biology. Spatial transcriptomics analysis of hAFSC-EV-injected kidneys showed that these EVs can reverse pathways altered during disease progression by stimulating proregenerative processes, specifically in the glomerulus, by regulating miR-93-5p targets. Alteration of glomerular endothelial cell transcriptomics and miR-93-5p targets was also confirmed in biopsies of patients with Alport syndrome using spatial molecular imaging. We demonstrated the critical role of miR-93-5p in glomerular endothelial cells and the capability of hAFSC-EVs to regulate miR-93-5p and its targets in Alport syndrome.

Humans↗
PubMed2026

Beyond Morphology: Reframing Lymph-Node Metastasis Prediction Through Clonal Ecology-Decades-Long Genomic Instability and Polyclonal-to-Monoclonal Transitions as the Missing Dimension in Cancer.

Recent whole-genome, lineage-tracing, single-cell, and spatial studies have reshaped our understanding of tumor evolution, revealing that cancers can arise from polyclonal populations, undergo decades-long genomic instability before clinical detection, and progress through dynamic changes in subclonal composition, cellular state, and ecological organization. These findings challenge the assumption underlying morphology-based prediction models that metastatic risk can be inferred from static histological features alone. Here, we revisit lymph-node metastasis prediction in colorectal cancer through clonal ecology, integrating computational pathology with evolutionary oncology. Drawing on the subclonal switchboard model proposed in 2012 and subsequent artificial intelligence (AI)-enabled approaches for tracking dominant and dormant subclones, we synthesize evidence that metastatic potential reflects clonal ancestry, evolutionary timing, spatial niche architecture, cellular plasticity, intercellular interactions, dormancy, and treatment-driven shifts in subclonal fitness. We define five complementary methodological pillars for operationalizing clonal ecology: single-cell transcriptomics for resolving rare subclones, evolutionary trajectories, and adaptive cell states; lineage tracing and phylogenetics for reconstructing clonal ancestry and divergence; spatial transcriptomics and genomics for mapping subclonal geography and tumor-stromal-immune interactions; longitudinal liquid biopsy surveillance for monitoring residual disease, clonal turnover, and emerging resistance; and AI-enabled multimodal integration for connecting histopathology, genomics, spatial biology, and longitudinal data into predictive ecological-state models. Multiple-instance learning and pathology foundation models provide scalable computational foundations for evolution-aware prediction. Translationally, dormant subclones represent actionable reservoirs of recurrence. A longitudinal clinical and experimental study of KMT2A-rearranged acute myeloid leukemia further supports central predictions of the subclonal switchboard framework by demonstrating treatment-associated shifts in subclonal dominance, persistence of cryptic adaptive programs, and ecological rewiring during resistance and relapse. We propose clonal ecology as a measurable dimension for extending morphology-driven prediction toward integrative models that anticipate evolutionary transitions, identify therapeutic windows, and proactively constrain adaptive tumor ecosystems before resistant or metastatic subclones achieve clinical dominance.

Humans↗
PubMed2003

Using network models to approximate spatial point-process models.

Spatial effects are fundamental to ecological and epidemiological systems, yet the incorporation of space into models is potentially complex. Fixed-edge network models (i.e. networks where each edge has the same fixed strength of interaction) are widely used to study spatial processes but they make simplistic assumptions about spatial scale and structure. Furthermore, it can be difficult to parameterize such models with empirical data. By comparison, spatial point-process models are often more realistic than fixed-edge network models, but are also more difficult to analyze. Here we develop a moment closure technique that allows us to define a fixed-edge network model which predicts the prevalence and rate of epidemic spread of a continuous spatial point-process epidemic model. This approach provides a systematic method for accurate parameterization of network models using data from continuously distributed populations (such as data on dispersal kernels). Insofar as point-process models are accurate representations of real spatial biological systems, our example also supports the view that network models are realistic representations of space.

Animals↗