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Results for “Spatial heterogeneity”

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At least 19 recordsLinked to original sources
PubMed1991

Bifurcating spatially heterogeneous solutions in a chemotaxis model for biological pattern generation.

We consider a simple cell-chemotaxis model for spatial pattern formation on two-dimensional domains proposed by Oster and Murray (1989, J. exp. Zool. 251, 186-202). We determine finite-amplitude, steady-state, spatially heterogeneous solutions and study the effect of domain growth on the resulting patterns. We also investigate in-depth bifurcating solutions as the chemotactic parameter varies. This numerical study shows that this deceptively simple-chemotaxis model can produce a surprisingly rich spectrum of complex spatial patterns.

Animals↗
PubMed1992

Spatial heterogeneity of the metabolic response of RIF-1 tumors to a vasoactive agent evaluated in vivo by one-dimensional 31P chemical-shift imaging.

Localized 31P NMR spectroscopy was used to evaluate the spatial heterogeneity of the metabolic response of RIF-1 tumors to hydralazine. Volume localized 31P spectra were obtained from subcutaneous RIF-1 tumors using one-dimensional chemical-shift imaging, before and 20 min after treatment with 5 mg/kg hydralazine, administered intravenously. Following treatment all of the tumors showed an overall decrease in the ratio of nucleoside triphosphate (NTP) to inorganic phosphate (Pi) and a decrease in pH. However, spatial localization revealed that the reduction in NTP/Pi was not uniform within some tumors. This was partly due to regional differences in the levels of metabolites existing before treatment. Normal tissue adjacent to the tumor did not show a significant decrease in high-energy metabolites or pH.

Animals↗
PubMed1990

Fractal properties of pulmonary blood flow: characterization of spatial heterogeneity.

The heterogeneity of pulmonary blood flow was examined using a fractal analytic procedure, and the results were compared with the traditional gravitational model of flow distribution. 99mTc-labeled macroaggregate was injected intravenously at functional residual capacity in six supine anesthetized dogs. The lungs were fixed in situ and sliced in transverse sections. The slices were imaged on a planar gamma camera, and a three-dimensional array of blood flow measurements was reconstructed for each lung. Fractal analysis was used to examine the spatial heterogeneity or RDs (relative dispersion = SD/mean) as a function of the number of pieces into which the flow array was subdivided. RDs was fractal and could be characterized by a fractal dimension (Ds) of 1.09 +/- 0.02, where a Ds of 1.0 reflects homogeneous flow and 1.5 indicates a random flow distribution. The data fit the fractal model exceptionally well with an average r = 0.98. RDs was examined in gravitational and isogravitational planes and as expected was greatest in the gravitational direction. However, the difference was small, suggesting that gravitation plays a secondary role to an underlying process producing heterogeneity. Within the limits of resolution attained by this study (piece volumes greater than 0.25 cm3), the heterogeneity of pulmonary blood flow is well characterized by a fractal model.

Animals↗
PubMed2021

Dissecting spatial heterogeneity and the immune-evasion mechanism of CTCs by single-cell RNA-seq in hepatocellular carcinoma.

Little is known about the transcriptomic plasticity and adaptive mechanisms of circulating tumor cells (CTCs) during hematogeneous dissemination. Here we interrogate the transcriptome of 113 single CTCs from 4 different vascular sites, including hepatic vein (HV), peripheral artery (PA), peripheral vein (PV) and portal vein (PoV) using single-cell full-length RNA sequencing in hepatocellular carcinoma (HCC) patients. We reveal that the transcriptional dynamics of CTCs were associated with stress response, cell cycle and immune-evasion signaling during hematogeneous transportation. Besides, we identify chemokine CCL5 as an important mediator for CTC immune evasion. Mechanistically, overexpression of CCL5 in CTCs is transcriptionally regulated by p38-MAX signaling, which recruites regulatory T cells (Tregs) to facilitate immune escape and metastatic seeding of CTCs. Collectively, our results reveal a previously unappreciated spatial heterogeneity and an immune-escape mechanism of CTC, which may aid in designing new anti-metastasis therapeutic strategies in HCC.

Aged↗
PubMed1990

Profound spatial heterogeneity of coronary reserve. Discordance between patterns of resting and maximal myocardial blood flow.

We examined the ability of individual regions of the canine left ventricle to increase blood flow relative to baseline rates of perfusion. Regional coronary flow was measured by injecting radioactive microspheres over 90 seconds in seven anesthetized mongrel dogs. Preliminary experiments demonstrated a correlation between the regional distributions of blood flow during asphyxia and pharmacological vasodilatation with adenosine (mean r = 0.75; 192 regions in each of two dogs), both of which resulted in increased coronary flow. Subsequent experiments, during which coronary perfusion pressure was held constant at 80 mm Hg, examined the pattern of blood flow in 384 regions (mean weight, 106 mg) of the left ventricular free wall during resting flow and during maximal coronary flow effected by intracoronary adenosine infusion. We found that resting and maximal flow patterns were completely uncorrelated to each other in a given dog (mean r = 0.06, p = NS; n = 3 dogs). Furthermore, regional coronary reserve, defined as the ratio of maximal to resting flow, ranged from 1.75 (i.e., resting flow was 57% of maximum) to 21.9 (resting flow was 4.5% of maximum). Thus, coronary reserve is spatially heterogeneous and determined by two distinct perfusion patterns: the resting (control) pattern and the maximal perfusion pattern. Normal hearts, therefore, contain small regions that may be relatively more vulnerable to ischemia. This may explain the patchy nature of infarction with hypoxia and at reduced perfusion pressures as well as the difficulty of using global parameters to predict regional ischemia. Despite the wide dispersion of coronary reserve, we found, by autocorrelation analysis, that reserve in neighboring regions (even when separated by a distance of several tissue samples) was significantly correlated. This also applied to patterns of resting myocardial flow. Thus, both resting coronary blood flow and reserve appear to be locally continuous and may define functional zones of vascular control and vulnerability, respectively.

Adenosine↗
PubMed1990

Spatial heterogeneity in striated muscle arteriolar tone, cell flow, and capillarity.

Spatial variations in microvascular function are described at two tissue sites in hamster cremaster muscle (pentobarbital sodium, 70 mg/kg ip). Arterioles observed include terminal arterioles and their feeding vessels, termed capillary network controllers (CNC). Although terminal arterioles at both sites had similar maximum diameters and cell flows, those at site I were significantly more constricted at rest (2.7 +/- 0.3 vs. 5.1 +/- 0.3 microns at site II) and showed lower resting flows (19.0 +/- 5.5 vs. 174 +/- 34 cells/s at site II). There were no spatial differences in CNC maximal parameters or CNC resting tone, yet CNC resting flow at site II (798 +/- 118 cells/s) significantly exceeded the value at site I (460 +/- 85 cells/s). At rest, median capillary cell flow at site I (3.3 cells/s) was half that at site II (6.3 cells/s). During hyperemia, perfused capillary segment length per unit volume was 84% greater at site I and estimated tissue erythrocyte content nearly double that at site II. Thus significant spatial differences in microvascular function exist in cell flow and vessel tone among terminal arterioles, in cell flow among CNC, and in capillarity and indices of capillary exchange.

Animals↗
PubMed1990

Spatial heterogeneity of intracellular Ca2+ concentration in nonbeating guinea pig ventricular myocytes.

The spatial distribution of intracellular Ca2+ concentration was determined by fluorescent digital imaging microscopy in fura-2-loaded quiescent cardiac myocytes isolated from guinea pig ventricle. Fluorescent ratio images revealed discrete as well as clustered bright fluorescent spots ("hot spots"), which occupied approximately 20-50% of an individual cell's area. The fluorescent intensity and the area of the hot spots were increased by agents that deplete Ca2+ in the sarcoplasmic reticulum, namely, ryanodine (20-40 nM) and caffeine (5-15 mM). However, when cells were exposed to agents that deplete mitochondrial Ca2+, such as the protonophore, carbonyl cyanide m-chlorophenyl-hydrazone (CCCP, 100-300 nM), or the inhibitor of electron transport, antimycin A (4-40 nM), the fluorescent intensity and the area of the hot spots were reduced. These results indicate that the spatial distribution of intracellular Ca2+ concentration in the ventricular myocytes of guinea pig is quite heterogeneous. The ability of CCCP and antimycin A, but not of caffeine and ryanodine, to reduce the fluorescent intensity in the hot spots implies that Ca2+ compartmentation in the mitochondria is largely responsible for the intracellular Ca2+ heterogeneity seen in the present study.

Animals↗
PubMedDate not supplied

Spatial heterogeneity of mitochondrial DNA and allozymes among populations of white-tailed deer and mule deer.

A white-tailed deer (Odocoileus virginianus) population in northeastern Minnesota and a mule deer (O. hemionus) population in the Bridger Mountains Montana, have previously been shown to be spatially subdivided into contiguous subpopulations. We assessed the degree of genetic differentiation among subpopulations and tested the hypothesis that differentiation will be greater for mitochondrial DNA (mtDNA) than for nuclear-encoded allozymes. Differentiation of the white-tailed deer subpopulations was significant for two allozyme loci but not for mtDNA, and the overall degree of differentiation was low. Gene flow, recent founding of the subpopulations, and polygamous breeding structure may all have contributed to this pattern. Greater differentiation was evident among disjunct populations than between the contiguous subpopulations of white-tailed deer. The contiguous mule deer subpopulations were significantly differentiated for mtDNA and one allozyme locus. Differentiation was greater for mtDNA than for allozymes. These results are consistent with demographic data that indicate mule deer males disperse more than do females. Disjunct mule deer populations may be similar or dramatically different in mtDNA haplotype frequencies that do not necessarily vary with geographic distance. Current and historical gene flow and breeding structure will influence population genetic patterns.

Animals↗
PubMedDate not supplied

[Spatially heterogeneous distribution of phytoplankton in a model of a regulated population].

With the help of the mathematical model is shown that the existence of the phitoplankton's mechanism of growth-speed regulation by means of excretion to the environment of biologically active substances, may lead to a considerable inhomogenity of it's spatial distribution, that is, patchness. There appears an intensive crowding of phitoplankton with homogenious distribution of nutrients, while some limitations of excretion rate and of dispersion coefficients are taken into account.

Mathematics↗
PubMed2025

Deep Learning on Histologic Slides Accurately Predicts Consensus Molecular Subtypes and Spatial Heterogeneity in Colon Cancer.

Colon cancer (CC) is the third most prevalent cancer type. It is highly heterogeneous, particularly in terms of molecular profiles, which have both prognostic and predictive impacts on the treatment efficacy. However, CC treatment in adjuvant situations is currently guided solely by T and N staging. In this context, consensus molecular subtypes (CMSs) were introduced to stratify patients with CC based on molecular profiles. Recent studies have shown that CMS can be heterogeneous in CC, leading to a worse prognosis. This study focused on predicting CMS and its heterogeneity in CC using deep learning on digitized hematoxylin and eosin ± saffron-stained whole-slide images. Data and whole-slide images of 1996 patients from the PETACC-8, The Cancer Genome Atlas-COAD, and PRODIGE-13 cohorts were used. The model is trained to predict a 4-dimensional CMS vector, reflecting intratumor heterogeneity (ITH). It comprises a self-supervised model for embedding image patches into vectors and a weakly supervised model predicting CMS calls. Ground-truth CMS scores are obtained with the CMSclassifier package. Interpretability analyses are performed at the slide and patch levels. For homogeneous tumors, the model trained on PETACC-8 achieves 93.0% (±1.4%) macroaverage area under the curve in internal cross-validation and 94.4% macroaverage area under the curve in external validation over PRODIGE-13, whereas the The Cancer Genome Atlas-COAD model reaches 85.4% (±3.0%) in cross-validation and 92.4% over PRODIGE-13. The trained models also provide spatial distributions of CMS across tumor slides and associate specific histologic features with each CMS. Finally, the models are able to predict ITH. The results show that a deep learning model trained on routine histology slides is capable of providing an efficient and robust method for predicting CMS and characterizing a patient's ITH, paving the way for the routine consideration of CMS/ITH in clinical decision making in the adjuvant setting.

Humans↗
PubMed2026

Integrated single-cell and spatial transcriptomic analyses reveal malignant epithelial glycolytic heterogeneity and spatial niche remodeling during colorectal cancer progression.

Colorectal cancer (CRC) progression is shaped by metabolic reprogramming and complex interactions within the tumor microenvironment. However, the cellular heterogeneity, spatial organization, and clinical relevance of glycolytic activity in CRC remain incompletely understood. In this study, we integrated single-cell RNA sequencing, bulk transcriptomics, and spatial transcriptomics data to systematically characterize glycolytic heterogeneity in CRC. Glycolytic activity was quantified using five independent scoring methods, consistently showing that epithelial cells exhibited the highest glycolytic activity across the two single-cell cohorts. Stratification of CopyKAT-verified aneuploid malignant epithelial cells into high-glycolysis (HG) and low-glycolysis (LG) subgroups by glycolysis scores revealed that HG cells exhibited higher stemness scores and chromosomal copy number variations. Cell-cell communication analysis revealed that, compared with LG cells, HG cells exhibited increased interaction frequency and strength with immune and stromal populations, indicating enhanced malignant epithelial-microenvironment crosstalk. Spatial transcriptomics analyses further revealed that glycolytic activity varied across normal colorectal tissue, primary CRC, and colorectal liver metastases, accompanied by progressive remodeling of epithelial-associated spatial niches and MIF-mediated intercellular communication. Bulk transcriptomic analysis identified a glycolysis-related prognostic signature with robust predictive performance, which served as an independent prognostic factor for overall survival in CRC cohorts. Collectively, these findings indicate that glycolytic heterogeneity is a key feature of CRC malignant epithelial cells and is closely associated with tumor progression, microenvironmental remodeling, and clinical outcomes.

Humans↗
PubMed1989

Fractal nature of regional myocardial blood flow heterogeneity.

Spatial variation in regional flows within the heart, skeletal muscle, and in other organs, and temporal variations in local arteriolar velocities and flows is measurable even with low resolution techniques. A problem in the assessment of the importance of such variations has been that the observed variance increases with increasing spatial or temporal resolution in the measurements. This resolution-dependent variance is now shown to be described by the fractal dimension, D. For example, the relative dispersion (RD = SD/mean) of the spatial distribution of flows for a given spatial resolution, is given by: RD(m) = RD(mref).[m/mref]1-Ds where m is the mass of the pieces of tissue in grams, and the reference level of dispersion, RD(mref), is taken arbitrarily to be the RD found using pieces of mass mref, which is chosen to be 1 g. Thus, the variation in regional flow within an organ can be described with two parameters, RD(mref) and the slope of the logarithmic relationship defined by the spatial fractal dimension Ds. In the heart, this relation has been found to hold over a wide range of piece sizes, the fractal Ds being about 1.2 and the correlation coefficient 0.99. A Ds of 1.2 suggests moderately strong correlation between local flows; a Ds = 1.0 indicates uniform flow and a Ds = 1.5 indicates complete randomness.

Animals↗
PubMed1992

Cytosolic and intranuclear calcium signals in rat basophilic leukemia cells as revealed by a confocal fluorescence microscope.

A confocal fluorescence microscope with an argon-ion laser (488 nm) and a He-Cd laser (325 nm) was used to study spatial heterogeneity of the calcium signals in rat basophilic leukemia 2H3 cloned cell line (RBL-2H3). After stimulation with antigen (2,4-dinitrophenol-conjugated bovine serum albumin), fluo-3-fluorescence intensities increased in individual RBL-2H3 cells with different lag times. Time-dependent profiles of the fluo-3-fluorescence intensities resembled closely the patterns of the sequential fluorescence-ratio images of fura-2, which were used to measure the intracellular free-calcium concentration ([Ca2+]i) in individual RBL-2H3 cells using a conventional fluorescence microscope. The present results obtained using the confocal fluorescence microscope showed spatial heterogeneities of fluo-3-fluorescence intensities, suggesting the existence of spatial heterogeneity of [Ca2+]i in RBL-2H3 cells. That is, the results showed that calcium signals first occurred transiently at pseudopodia in RBL-2H3 cells, then the signals transferred to the central parts of the cells. In addition, from the fluorescence images of co-loaded Hoechst 33342 (bisbenzimide H 33342, a DNA-specific probe) which were produced by excitation with a He-Cd laser, it was found that the fluorescence images of the nucleus were quite similar to those of the calcium signals mentioned above. This suggested that the receptor-mediated calcium signals were transferred not only to the cytoplasm but also to the nucleus.

Animals↗
PubMed2026

Accurately Deciphering Tissue Heterogeneity From Spatial Multi-Modal and Multi-Omics With STransformer.

Advances in spatially resolved technologies enable the simultaneous acquisition of diverse data modalities within a tissue slice while preserving critical spatial context, which presents unprecedented opportunities to decipher intricate tissue heterogeneity. However, existing computational approaches lack the intrinsic flexibility to universally process both spatial multi-modal and multi-omics data. Here, we introduce STransformer, a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short-range cellular interactions and tissue-wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity. Systematic evaluations across diverse species, tissue types, and data modalities highlight its profound versatility. For spatial multi-modal data, STransformer delineates intricate anatomical structures in the human cortex, uncovers pathological mechanisms in Alzheimer's disease, and characterizes dynamic spatiotemporal developmental trajectories during chicken cardiogenesis. Scaling to spatial multi-omics data, STransformer synergizes spatial transcriptomic and proteomic profiles to decipher intricate immune microenvironments within the human tonsil, and jointly analyzes spatial epigenomic and transcriptomic data to infer regulatory mechanisms in the mouse embryonic brain. Consequently, STransformer serves as a highly versatile and robust analytical framework for advancing our understanding of tissue heterogeneity and disease pathogenesis.

Multiomics↗