Spatial Heterogeneity Research Articles

Abstract PS05-04: [89Zr]Trastuzumab-PET/MRI to Characterize HER2+ Breast Cancer: A Quantitative Approach on Tumor Heterogeneity

Abstract Introduction: Molecular imaging of human epidermal receptor 2 (HER2) aims to overcome limitations of traditional HER2 assessment through biopsy, including invasiveness and inability to detect intra and inter-tumoral spatial heterogeneity. Prior human studies suggest that [89Zr]Trastuzumab-positron emission tomography (PET) imaging can effectively differentiate HER2 lesions (Dehdashti et al, Breast Cancer Res. Treat. 2018). Commonly, CT complements PET for anatomical reference, however, integrating MRI enables the sensitivity of soft-tissue contrast required for anatomic and morphological breast imaging and can provide for quantitative multiparametric characterization. Diffusion weighted-MRI (DW-MRI) contributes to tumor characterization by assessing intratumoral cellularity via the apparent diffusion coefficient (ADC), and can be combined with molecular expression from HER2-PET. We present preliminary results in 13 patients with HER2 PET/MRI to define tumor and normal tissue imaging metrics. Methods: A phase II clinical trial assessing the feasibility of [89Zr]trastuzumab-PET with simultaneous quantitative DW-MRI to enhance understanding of tumor heterogeneity in patients with HER2-positive metastatic breast cancer. 13 patients (ages 40-70; mean 60) with HER2-positive breast cancer based on prior biopsy underwent whole-body [89Zr]trastuzumab-PET/MR imaging (5 ± 1 days post-injection of radiopharmaceutical) during the course of HER2-directed therapy. Normal organ and tumor regions of interest (ROI) were identified on concurrently acquired whole-body T1-weighted MRI for ADC (cellularity) and standardized uptake value (SUV, PET uptake) mean quantification. Tumor presence was confirmed via bone scintigraphy, FDG-PET/CT, or contrast-enhanced MRI. Non-parametric T-tests compared lesions to normal organs. Lesions greater than 30 mm in diameter underwent multiparametric intratumoral habitat analysis. Using the median HER2 values, tumors were evaluated for heterogeneity of high and low HER2 expression in conjunction with ADC. Long-term treatment response evaluation is ongoing. Results: Mean [89Zr]trastuzumab uptake, SUV, and ADC values for normal tissue were summarized in Table 1. All tumors demonstrated higher overall uptake of [89Zr]trastuzumab (bone: p=0.019, brain: p=0.014, breast: p=0.069, juxtapulmonary: p=0.026) and increased ADCmean values (bone: p=0.002, brain: p=0.5, breast: p=0.03, juxtapulmonary: p=0.037), in comparison to matched normal organs. Notably, one of five patients with a breast lesion, who completely responded to HER2 targeted therapy, exhibited the highest breast lesion SUVmean. Brain and lymph node lesions demonstrated intratumoral heterogeneity of HER2 expression. Conclusion: Our study demonstrates the potential value of quantitative MRI along with molecular imaging to characterize metastatic HER2+ breast cancer and evaluate intratumoral heterogeneity. We underscore the importance of standardizing processing techniques and contribute to this effort by summarizing [89Zr]trastuzumab uptake and cellularity values of normal physiological uptake. Higher SUVmean and ADC mean values observed in lesions, compared to normal tissue, highlight their potential roles in intratumoral classification. While studies have shown the utility of [89 Zr]trastuzumab-PET/CT, our findings demonstrate that integrated DW-MRI can aid in tumor classification. Table 1: Physiological 89Zr-Trastuzumab Uptake (SUVmean) and Apparent Diffusion Coefficient (ADCmean) in Healthy Tissues Citation Format: Ameer Mansur, Moozhan Nikpanah, Johnathan McConathy, Erica Stringer-Reasor, Gabrielle Rocque, Ahmed Elkhanany, Katia Khoury, Nusrat Jahan, Suzanne Lapi, Anna Sorace. [89Zr]Trastuzumab-PET/MRI to Characterize HER2+ Breast Cancer: A Quantitative Approach on Tumor Heterogeneity [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS05-04.

Does digital economy agglomeration promote green economy efficiency? A spatial spillover and spatial heterogeneity perspective

Does digital economy agglomeration promote green economy efficiency? A spatial spillover and spatial heterogeneity perspective

Evolution Model and Driving Mechanism of Urban Logistics Land: Evidence from the Yangtze River Delta

Logistics land is the spatial carrier for the development of logistics enterprises. Its evolution mode and driving mechanism determine the level of high-quality development of the logistics industry, and serve as an important basis for urban planning and territorial spatial planning. This study introduced a Boston consulting group (BCG) matrix and geographically weighted regression (GWR) spatial econometric models to carry out empirical research on the Yangtze River Delta (YRD), in an effort to provide scientific information for evidence-based decision-making by governments and enterprises. The scale and ratio of logistics land (LLS and LLR) in the YRD showed significant spatial heterogeneity and autocorrelation, cities with large logistics land use converging from clusters to belts from 2000 to 2020, and agglomerations with high logistics land ratio (LLR) migrating from inland to coastal areas. Diversified models of logistics land evolution also emerged, such as high scale–high speed cities, low scale–low speed cities, high scale–low speed cities, and low scale–high speed cities. In addition, the driving mechanism of LLS and LLR was very complex, with a great difference in the intensity, nature and spatial effects of the influence of different factors. The inspiration from empirical case studies is urgent to revise the planning norms and clarify the LLS and LLR control standards for logistics land use. Meanwhile, the synergistic development target of the logistics industry in the new era is changing from the manufacturing industry to the commerce and trade industry; the establishment of planning zoning and the designing of differentiated management policies significantly improve the planning applicability.

Abstract PS16-10: SPATIAL IMMUNE CELL DISTRIBUTION CAN REFINE PROGNOSIS IN EARLY-STAGE ER+/HER2-/LN- BREAST CANCER

Abstract Lymphocytic infiltrate is a known prognostic biomarker in estrogen receptor(ER)-negative breast cancers (BCs). Comparatively ER+ disease is putatively cold, however, there exists an infiltrate-rich subset of ER+ tumours with significant spatial heterogeneity and unknown clinical impact. Using serial sections taken from early-stage, ER+/HER2- breast tumours of Irish patients enrolled in the TAILORx trial (n=450), we aimed to investigate the prognostic potential of markers encompassing tumour architecture. Immunohistochemistry for Ki67 and CD45 (leukocyte common-antigen), and staining for haematoxylin and eosin was applied to all sections [1]. Classifiers for stromal fraction (SF), stromal-infiltrate (sTIL), Ki67-LI, and their spatial relationships within the tumour were generated using QuPath [2] and R Studio. Trained marker classifiers were validated against an expert pathologist (R2 of M-Score to: CD45%: 0.968, Ki67-LI: 0.814, sTIL: 0.864) to define observed lymphocytes as tumour or stromal-infiltrating, retain only tumour Ki67+ density, and to investigate SF. Cohort mean SF was 67.69% (range 16.35 – 98.29%), with marginally significant differences in recurrence prediction for cohort high v low SF by mean (c-index = 0.58, p< 0.032), and luminal A disease (p=0.037) only. sTILs did not differ significantly between high/low mean SF (Mann-Whitney p=0.6201), though sTIL was prognostic in the OncotypeDx intermediate Recurrence Score (RS) category overall (p=0.0076). This trend appeared strongest in intermediate RS patients receiving chemo-endocrine therapy (HT+CT) (p < 0.0001) vs endocrine therapy (HT) alone (p=0.86). Investigating the effects of prescribed therapy on sTIL-derived recurrence risk also revealed significant trends in those patients receiving HT+CT only (p < 0.00001) vs HT alone (p=0.26). Spatial analysis of sTILs suggest that tumours become more immune excluded as Oncotype Dx RS increases - particularly from intermediate to high RS (Wilcoxon Intermediate v High: p=0.0077), with significant differences in survival for high/low tumour-immune hotspots observed in Intermediate RS, HT+CT treated patients (p=0.0052). Further spatial analysis suggests that high normalised frequency of infiltrate [method adapted from 3] (within 7um of tumour cells) have negative prognostic impact for premenopausal patients (p=0.017), and inter-sectional analysis identifies niche tumour environments where high Ki67-LI colocalize with immune infiltrates[methods adapted from 4, 5], most notable in Intermediate RS tumours.. Overall these data suggest immune-spatial subsets can be used to refine risk stratification of ER+ breast cancer.

Multiplexed Imaging Mass Cytometry Analysis Characterizes the Vascular Niche in Pancreatic Cancer.

Oncogenesis and progression of pancreatic ductal adenocarcinoma (PDAC) is driven by complex interactions between the neoplastic component and the tumor microenvironment (TME), which includes immune, stromal, and parenchymal cells. In particular, most PDACs are characterized by a hypovascular and hypoxic environment that alters tumor cell behavior and limits the efficacy of chemotherapy and immunotherapy. Characterization of the spatial features of the vascular niche could advance our understanding of inter- and intra-tumoral heterogeneity in PDAC. Here, we investigated the vascular microenvironment of PDAC by applying imaging mass cytometry using a 26-antibody panel on 35 regions of interest (ROIs) across 9 patients, capturing over 140,000 single cells. The approach distinguished major cell types, including multiple populations of lymphoid and myeloid cells, endocrine cells, ductal cells, stromal cells, and endothelial cells. Evaluation of cellular neighborhoods identified 10 distinct spatial domains, including multiple immune and tumor-enriched environments as well as the vascular niche. Focused analysis revealed differential interactions between immune populations and the vasculature and identified distinct spatial domains wherein tumor cell proliferation occurs. Importantly, the vascular niche was closely associated with a population of CD44-expressing macrophages enriched for a pro-angiogenic gene signature. Together, this study provides insights into the spatial heterogeneity of PDAC and suggests a role for CD44-expressing macrophages in shaping the vascular niche.

Abstract PS09-08: Genomic characterization of endocrine resistance in ER+HER2+ breast cancers in the POETIC Trial

Abstract Background: Mechanisms of resistance to endocrine therapy are not well understood within ER+HER2+ breast cancer (BC). Our prior work suggested that intrinsic HER2-Enriched (HER2E) molecular subtype predicts early resistance to aromatase inhibitors (AI) (Bergamino eBioMedicine 2022) and high on-treatment (on-Txt) Ki67 levels predict poor survival (Smith Lancet Oncol 2020). Improved early detection of persistent proliferating tumor cells with endocrine resistance pathways could be targeted by pre-emptive personalized therapy and reduction in recurrence. In this study, we proposed to further identify additional alterations/features from genomic and spatial data to provide unprecedented new insight into intrinsic and adaptive resistant pathways in tumor cells that may assist to identify molecular targets for treatment. Materials: POETIC was a phase III trial of post-menopausal patients with ER/PR+ invasive BC (n = 4480) randomized 2:1 to 2 weeks of peri-operative AI (POAI) vs control, followed by standard-of-care treatment. Ki67 was assessed by IHC and intra-tumor heterogeneity was evaluated (5-15 regions) for all the POETIC POAI samples (N = 2487). ER+HER2+ samples were classified as good responders (GR) or poor responders (PR) based on a reduction in Ki67 between pre-treatment (pre-Txt) and 2-week on-Txt samples. Tumor-infiltrating lymphocytes were assessed; multiplex Immunofluorescence (mIF) was performed to measure immune cell densities in tumor and stroma compartments (CD3, CD20, CD68, FOXP3, and CD3 FOXP3 co-expression). Gene expression profiles by BC360™ (Nanostring) on all 210 pairs of POAI treated ER+/HER2+; whole exome sequencing (WES, 100X) were performed on pre-Txt tumor and blood samples from 13 GR, 17 PR, and 9 HER2E GR. We performed GeoMx Whole Transcriptome on 4 pairs (pre-Txt and on-Txt) of GR and GeoMx Proteins (77 including IO proteins) on 6 pairs of GRs and 6 pairs of PRs. Results: The most frequently mutated genes were TP53, PIK3CA, GATA3, and CHD4. Only TP53 was associated with PR (Fisher’s exact p=0.01). TP53 mutated cases had higher expression of TP53 mutant-like gene expression signature compared to wild-type cases (Wilcoxon test p=0.001), mIF FOXP3 (Wilcoxon test p = 0.0005), and CD68 (Wilcoxon test p = 0.019) density score. However, within the HER2-E subset, we found that TP53 mutations were associated with GR (Fisher’s exact p=0.02). We found spatial heterogeneity of Ki67 IHC levels across POAI samples. Examining IHC, while there was higher heterogeneity of Ki67 in the ER+HER2- samples (n = 2264) with 3% of pre-Txt and 9% on-Txt, 6% of ER+HER2+ samples (13/223, 6 LumA, 5 LumB, and 2 HER2E) showed heterogeneity of Ki67 exclusively on-Txt. Even in GR tumors with Ki67 < 10% on-Txt, we identified hotspots with retained proliferating Ki67+ cells after 2 weeks of POAI. The lobular tumors were GR and had characteristic CDH1 mutations. Importantly, cases with persistent areas of Ki67+ cells, regardless of Her2 status, were associated with late relapse. To further explore intratumoral heterogeneity, we performed spatial whole transcriptomics profiling on 95 regions from 4 pairs of GR samples (Ki67 > 10% at baseline and Ki67 < 10% on-Txt) and found low intratumoral heterogeneity in the pre-Txt samples that increased at 2 weeks on-Txt. In a larger set of samples including both GR and PR with the GeoMx protein method, we found increased intratumoral heterogeneity in the PR vs GR. Conclusion: While TP53 mutation was generally a predictor of poor response; in HER2-E it paradoxically was associated with a good early response to aromatase inhibitor which warrants further investigation. Ki67 levels in ER+HER2+ showed higher intratumoral heterogeneity in a subset of patients on treatment suggesting the potential of persistent, proliferating cells leading to later recurrence. Our spatial RNA and protein data further observe the intratumoral heterogeneity that identifies pathways for use as potential spatial biomarkers. Citation Format: Maggie Chon U Cheang, Xixuan Zhu, Orsolya Sipos, Anastasia Alataki, Mikayla Feldbauer, Elena López-Knowles, Holly Tovey, Lucy Kilburn, Milana Bergamino Sirvén, Dhrusti Patel, Hui Xiao, Perry Maxwell, Anthony Skene, Chris Holcombe, Manuel Salto-Tellez, Nicholas Turner, Andrew Dodson, Ian Smith, John Robertson, Judith Bliss, Gene Schuster, Roberto Salgado, Mitch Dowsett, Katherine A Hoadley. Genomic characterization of endocrine resistance in ER+HER2+ breast cancers in the POETIC Trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS09-08.

Spatial heterogeneity in tumor adhesion qualifies collective cell invasion

Collective cell invasion, a canon of most invasive solid tumors, is an emergent property of the interactions between cancer cells and their surrounding extracellular matrix (ECM). However, tumor populations invariably consist of cells expressing variable levels of adhesive proteins that mediate such interactions, disallowing an intuitive understanding of how tumor invasiveness at a multicellular scale is influenced by spatial heterogeneity of cell-cell and cell-ECM adhesion. Here, we have used a Cellular Potts model-based multiscale computational framework that is constructed on the histopathological principles of glandular cancers. In earlier efforts on homogenous cancer cell populations, this framework revealed the relative ranges of interactions, including cell-cell and cell-ECM adhesion that drove collective, dispersed, and mixed multimodal invasion. Here, we constitute a tumor core of two separate cell subsets showing distinct intra- and intersubset cell-cell or cell-ECM adhesion strengths. These two subsets of cells are arranged to varying extents of spatial intermingling, which we call the heterogeneity index (HI). We observe that low and high intersubset cell adhesion favors invasion of high-HI and low-HI intermingled populations with distinct intrasubset cell-cell adhesion strengths, respectively. In addition, for explored values of cell-ECM adhesion strengths, populations with high HI values collectively invade better than those with lower HI values. We then asked how spatial invasion is regulated by progressively intermingled cellular subsets that are epithelial, i.e., showed high cell-cell but poor cell-ECM adhesion, and mesenchymal, i.e., with reversed adhesion strengths to the former. Here too, intersubset adhesion plays an important role in contextualizing the proportionate relationship between HI and invasion. An exception to this relationship is seen for cases of heterogeneous cell-ECM adhesion where sub-maximal HI patterns with higher outer localization of cells with stronger ECM adhesion collectively invade better than their relatively higher-HI counterparts. Our simulations also reveal how adhesion heterogeneity qualifies collective invasion, when either cell-cell or cell-ECM adhesion type is varied but results in an invasive dispersion when both adhesion types are simultaneously altered.

Cracking the code: Spatial heterogeneity as the missing piece for modeling granular fluidized bed drying

Pharmaceutical twin-screw wet granulation is a multifaceted and intricate process pivotal to drug product development. Accurate modeling of this process is indispensable for optimizing manufacturing parameters and ensuring product quality. The fluid bed dryer, an integral component of this granulation process, significantly influences the granular critical quality attributes. This study builds upon prior research by integrating experimental findings on granule segregation during fluid bed drying into an existing compartmental model, enhancing its predictive capabilities. An additional model layer on granule segregation behavior is composed and integrated into the existing model structure in this study. The added model compartment describes probability distributions on the vertical position of granules within each granule size class considered. To beware of overfitting, predictions of both the moisture content after drying and the granule bed temperature throughout drying are discussed in this study relative to experimental data from earlier published studies. These independent analyses demonstrated a marked improvement in prediction accuracy compared to earlier published model structures. The refined model accurately predicts the residual moisture content after drying for an untrained formulation. Moreover, it simultaneously makes accurate predictions of the granular bed temperature, which emboldens its structural correctness. This advancement makes it a powerful tool for predicting the behavior of the pharmaceutical fluid bed drying, which holds significant promise to facilitate pharmaceutical product development.

Periodic solutions of an NPZ model with periodic delay and space heterogeneity

In this paper, we investigate a nutrient-phytoplankton-zooplankton (NPZ) model with seasonality and spatial heterogeneity, in which the immature zooplankton with size structure is described by the quasi-linear first-order partial differential equation. A three-dimensional periodic delay food chain model with initial value is derived from the original model. To establish the threshold dynamics of NPZ model, we first obtain the global attractivity of the positive periodic solution of the nutrient-phytoplankton (NP) subsystem by using the method of sub-super solutions and associated iterations. We then give the integral expression of threshold for the corresponding system, which is convenient for numerical simulations. Based on this, the threshold dynamics is discussed by appealing to the comparison arguments and the persistence theory. Finally, the analytic results are in good consistence with our numerical simulations.

Identifying interactive effects of spatial drivers in soil heavy metal pollutants using interpretable machine learning models

The accurate identification of spatial drivers is crucial for effectively managing soil heavy metals (SHM). However, understanding the complex and diverse spatial drivers of SHM and their interactive effects remains a significant challenge. In this study, we present a comprehensive analysis framework that integrates Geodetector, CatBoost, and SHapley Additive exPlanations (SHAP) techniques to identify and elucidate the interactive effects of spatial drivers in SHM within the Pearl River Delta (PRD) region of China. Our investigation incorporated fourteen environmental factors and focused on the pollution levels of three prominent heavy metals: Hg, Cd, and Zn. These findings provide several key insights: (1) The distribution of SHM is influenced by the combined effects of various individual factors and interactions within the source–flow–sink process. (2) Compared with the spatial interpretation of individual factors, the interaction between Hg and Cd exhibited enhanced spatial explanatory power. Similarly, interactions involving Zn mainly demonstrated increased spatial explanatory power, but there was one exception in which a weakening was observed. (3) Spatial heterogeneity plays a crucial role in determining the contributions of environmental factors to soil heavy metal concentrations. Although individual factors generally promote metal accumulation, their effects fluctuate when interactions are considered. (4) The SHAP interpretable method effectively addresses the limitations associated with machine-learning models by providing understandable insights into heavy metal pollution. This enables a comparison of the importance of environmental factors and elucidates their directional impacts, thereby aiding in the understanding of interaction mechanisms. The methods and findings presented in this study offer valuable insights into the spatial heterogeneity of heavy metal pollution in soil. By focusing on the effects of interactive factors, we aimed to develop more accurate strategies for managing SHM pollution.

Developing novel ensemble models for predicting soil hydraulic properties in China’s arid region

Accurately quantifying the mass (water, nutrients, and carbon) and energy exchange processes between the Earth’s atmosphere, biosphere, and lithosphere requires the accurate parameterization of soil hydraulic properties (SHPs) and their spatial heterogeneity. Because direct measurements of SHPs are difficult, time-consuming, and impossible at larger spatial scales, various pedotransfer functions (PTFs) have been developed in the last few decades, providing divergent estimates of SHPs from readily measurable variables. However, existing PTFs are mostly developed for specific regions and may not be suitable for other pedoclimatic conditions. Here, PTFs were developed using multiple machine-learning algorithms to estimate SHPs and examined the weaknesses and strengths of each method in estimating the average and variability of SHPs across China’s arid region. The optimal PTFs were applied to a 1 × 1 km2 regional map of texture and bulk density, thus producing maps of the saturated hydraulic conductivity (Ks), the parameters of the van Genuchten (VG) formulation, field capacity (θfc), wilting point (θwp), plant available water (θpa), and soil macroporosity (ϕm) in the 0–2 m soil profile throughout the region. The results indicate that the ensemble model with the averaging method (EMA) is the most robust for estimating all SHPs. The EMA-PTFs for Ks yielded the best performance for sand textures, followed by sandy loam, loam, silty loam, silty clay loam, loamy sand, and clay loam textures. There were no significant differences in estimating soil water retention curve parameters among the different soil texture classes. Using the same observed data set, we demonstrated that the new EMA-PTFs outperformed those of existing PTFs, such as Rosetta and HYPRES, with RMSE values decreasing by 25–83 % depending on the SHPs. Furthermore, our SHP datasets exhibited significantly deeper soil profiles and higher accuracy than other available regional and global SHP products. The VG retention parameter α shows the greatest variation vertically throughout the 0–2 m soil profile, followed by ln(Ks), θr, θpa, θfc, θwp, ϕm, θs and n. All SHPs exhibit much lower variability in the desert than in other areas, likely due to the homogeneous particle size distribution of desert areas. This study provides more accurate SHP estimates in China’s arid region than the existing SHP products by developing advanced PTFs and highlights the inconsistency in SHPs among different global or regional products; the uncertainties induced by PTFs should thus be considered in future terrestrial biosphere modeling.

Comprehensive analysis of spatial heterogeneity reveals the important role of the upper-layer fermented grains in the fermentation and flavor formation of Qingxiangxing baijiu

Different spatial positions lead to inconsistent fermentation effects and flavors, however the spatial heterogeneity of Qingxiangxing (QXX) Baijiu remains unknown. We investigated the microbes, flavors, and physicochemical properties of different layers in fermented grains of QXX Baijiu using Illumina HiSeq sequencing, two-dimensional gas chromatography–mass spectrometry (GC × GC–MS) and ultra-high performance liquid chromatography-mass (UHPLC-MS). A total of 79 volatiles, 1596 metabolites, 50 bacterial genera, and 52 fungal genera were identified. The contents distribution followed the order: upper layer > bottom layer > middle layer. Organic acids and derivatives were the main differential metabolites across the three layers. Starch, pH, and reducing sugar levels increased from the upper to bottom layer. Saccharomyces and Lactobacillus were dominant microbes. Pediococcus, the biomarker of upper layer, showed positively correlations with formic acid, ethyl lactate, acetic acid, ethyl linoleate, and ethyl oleate. These findings deepen our understanding of the fermentation and flavor formation mechanism of QXX Baijiu.

Underway pCO2 Surveys Unravel CO2 Invasion of Lake Superior From Seasonal Variability

AbstractThis study observed seasonal trends and inferred drivers of CO2 biogeochemistry at the air‐water interface of Lake Superior. Underway carbon dioxide partial pressure (pCO2) was measured in surface water during 69 transects spanning ice free seasons of 2019‐2022. These data comprise the first multiannual pCO2 time series in the Laurentian Great Lakes. Surface water pCO2 was closely tied to increasing atmospheric pCO2 over a 100‐day CO2 equilibration timescale, while seasonal variability was controlled equally by thermal and non‐thermal drivers during the ice‐free season. Comparison to previous modeling efforts indicated that Lake Superior surface pCO2 increased with two decades of rising atmospheric CO2. Spatial heterogeneity in CO2 dynamics was highlighted by a conductivity‐based delineation of “riverine” and “pelagic” regimes, each of which was associated with net CO2 influx over Julian days 100–300 on the order of 25 Gmol C. These findings refine previous estimates of Lake Superior C fluxes, support predictions of anthropogenic CO2 invasion during the ice‐free season, point to new observation strategies for large lakes, and highlight an urgent need for studies of changes to lacustrine C cycling.

Transport accessibility and hospital attributes: A nonlinear analysis of their impact on Women's prenatal care seeking behavior

Ensuring women receive vital prenatal care is crucial for maternal and newborn health. Limited research explores factors influencing prenatal care-seeking from a geospatial perspective. This study, based on a substantial Wuhan dataset (23,947 samples), investigates factors influencing prenatal care-seeking, focusing on transport accessibility and hospital attributes. Findings indicate a nuanced relationship: (1) A non-linear trend, resembling an inverted “U,” reveals the complex interplay between transport accessibility, hospital attributes, and prenatal care visits. Hospital attributes have a more pronounced impact than transport accessibility. (2) Interaction analysis underscores that lower prenatal care visits relate to low-income and education levels, despite reasonable public transport accessibility. (3) Spatial disparities are significant, with suburban areas facing increased obstacles compared to urban areas, particularly for those in suburban rural areas. This study enhances understanding by emphasizing threshold effects and spatial heterogeneity, offering valuable perspectives for refining prenatal care policies and practices.

Analysis of the spatiotemporal dynamics and driving factors of ecosystem quality in Inner Mongolia from 2005 to 2020

Enhancing ecosystem quality is a necessary part of establishing of ecological civilization. The study of ecosystem quality requires the development of comprehensive evaluation indices. The existing simple remote sensing ecological indices are insufficient for achieving a comprehensive and systematic evaluation of the ecosystem quality. Therefore, we constructed an ecosystem quality index based on the landscape pattern, ecosystem stability, and ecosystem services. The spatiotemporal dynamics of the ecosystem quality in Inner Mongolia were analyzed over the period from 2005 to 2020. Moreover, a geographically weighted regression model was used to investigate the factors influencing the spatiotemporal variations in the ecosystem quality. The main results are as follows. (1) The spatial distribution of ecosystem quality in Inner Mongolia exhibited a gradual decline from the northeast to the southwest. In contrast, temporal analysis revealed a general increase in ecosystem quality from 2005 to 2020. (2) Climate was a significant factor influencing the spatial heterogeneity and temporal variability of the ecosystem quality. Socioeconomic factors, population density and livestock numbers had notable impacts on the spatial heterogeneity and temporal variability of ecosystem quality, respectively. (3) In Inner Mongolia, temperature and ecosystem quality showed a positive correlation in the northeastern region, but a negative correlation in the central and western regions. The findings offer valuable support for local policymakers in making informed decisions regarding targeted ecosystem management. Furthermore, our results provide local governments with valuable insights for enhancing the quality of regional ecosystems by taking into account the specific conditions of the area.

Research on the restorative benefits of sky gardens in high-rise buildings based on wearable biosensors and subjective evaluations

BackgroundThe design of sky gardens in high-rise buildings to promote health has recently attracted increased attention. However, little is known about the specific physiologically and psychologically restorative benefits of sky gardens. MethodThis article defined sky garden types according to five indicators in three dimensions based on the characteristics of the high-rise buildings where sky gardens are located: plaza-park, rest-stay and move-pass sky gardens. Typical sky gardens of each type were selected for the subsequent experiment. Thirty-six participants experienced 12 typical case scenarios (432 pictures), and data were collected on physiological responses (skin conductance resistance, SCR; heart rate variability, HRV; electroencephalogram, EEG; and eye movement) and psychological evaluations (emotional valence & arousal self-esteem scale, perceived restrictiveness scale) during the sky garden spatial experience. ResultsThere are significant differences in plaza-park, rest-stay and move-pass type sky gardens, especially in the internal spatial characteristics (size scale, shape index, and elementary richness). The plaza-park sky gardens had better restorative outcomes in visual-physiological (average pupil diameter, average blink count), emotional valence and restrictiveness components of being away, fascination, and coherence. The rest-stay sky gardens had better restorative effects on SCR, HRV, emotional arousal, and compatibility. The move-pass sky gardens had the greatest restorative benefits in the average saccade count. ConclusionsSky gardens in high-rises impact people's physical and psychosocial well-being. The restorative qualities of the three types of sky gardens differ based on their spatial heterogeneity, with large-scale sky gardens, diverse natural landscapes, public facilities, and high void-to-solid ratios having greater restorative potential.

Urban vitality and built environment from the perspective of spatiotemporal heterogeneity

ABSTRACT The spatiotemporal heterogeneity of the built environment’s effects on urban vitality is analysed through geographically and temporally weighted regression models. It is found that residents’ travel time and patterns lead to temporal heterogeneity, which is manifested by the fluctuation of the environmental effect of the peak in the morning and evening and the difference between weekdays and weekends. This is especially evident in the business district. Spatial heterogeneity is mainly reflected in the difference between the new urban area and the old city area. Single-function green spaces in areas with high functional complexity still have a weak attraction to people. Land use mix, scale and location are rather nonstationary in the dimensions of time and space.

Spatial heterogeneity of soil potassium geochemistry: A case study from Tianfu New Area, Chengdu, China

Urban-rural integration zones, situated at the interface between urban and rural environments, undergo profound alterations in arable soil quality attributed to rapid urbanization and intensified agricultural practices. However, there is still insufficiency research on potassium depletion from a spatial perspective, despite the increasing demand for vegetables. To address this gap, the spatial distribution characteristics of soils potassium in Tianfu New District, Chengdu Plain, China, were studied based on geochemistry, geostatistics and Earth system science. The results showed that: (1) Spatial heterogeneity existed in both soil total potassium (STP) and soil available potassium (SAP). However, there was no obvious spatial correlation between STP and SAP, and their spatial extents exhibited minimal overlap. (2) The STP levels are mainly affected by the altitude, slope, stratum exposure and geological background. (3) The SAP content is obviously affected by anthropogenic input, and the enrichment is significantly affected by fertilizers. This study reinforces the notion that the human intervention has strongly affected arable soil quality. The availability of fertilizer (e.g., potash) may significantly affecting food security within China.

Assessing the accuracy of remote sensing data products: A multi-granular spatial sampling method

Over the past two decades, remote sensing data have demonstrated significant potential across various fields. Accuracy assessment, as a crucial component, plays a vital role in ensuring the effective application of remote sensing data products. To assess the accuracy of remote sensing data products, this paper proposed a multi-granular spatial sampling method (MG-SSM). In the proposed MG-SSM, the assessed remote sensing data products were stratified into different layers based on spatial heterogeneity, quantified by calculating the aggregation index. Subsequently, multi-granular sampling units were defined for each layer based on spatial correlation, quantified using Moran’s I and Z-score. Finally, the accuracy of remote sensing data products was assessed by comparing it with the reference data. Using the classification results of Landsat 9 OLI/TIRS with a 30-m spatial resolution as assessed data, and the classification results of Sentinel-2 MSI with a 10-m spatial resolution as reference data, and employing Overall Accuracy (OA) and the Kappa coefficient as assessment metrics, the performance of MG-SSM was compared against other sampling methods, including SRS, ST, SY, SSS, and GLCM. The performances of SRS, ST, SY, SSS, GLCM, and MG-SSM were 74.41%, 75.39%, 76.57%, 78.47%, 76.77%, and 67.36% in terms of overall accuracy, and 0.6, 0.61, 0.64, 0.66, 0.64, and 0.46 in terms of the Kappa coefficient, respectively. The results indicated that MG-SSM exhibited the lowest values for overall accuracy and the Kappa coefficient, aligning with the objective of assessing the accuracy of remote sensing data products. This outcome is attributed to MG-SSM’s strategy of distributing more sample points in areas with lower aggregation of land-cover classes, which are more prone to classification errors. Collectively, the proposed MG-SSM enhanced the representativeness and reduced the information redundancy of the sample points, making it an efficient sampling method for assessing the accuracy of remote sensing data products.

Modelling dynamics between free-living amoebae and bacteria.

Free-living amoebae (FLA) serve as hosts for a variety of endosymbionts, which are microorganisms that reside and multiply within the FLA. Some of these endosymbionts pose a pathogenic threat to humans, animals, or both. The symbiotic relationship with FLA not only offers these microorganisms protection but also enhances their survival outside their hosts and assists in their dispersal across diverse habitats, thereby escalating disease transmission. This review is intended to offer an exhaustive overview of the existing mathematical models that have been applied to understand the dynamics of FLA, especially concerning their interactions with bacteria. An extensive literature review was conducted across Google Scholar, PubMed, and Scopus databases to identify mathematical models that describe the dynamics of interactions between FLA and bacteria, as published in peer-reviewed scientific journals. The literature search revealed several FLA-bacteria model systems, including Pseudomonas aeruginosa, Pasteurella multocida, and Legionella spp. Although the published mathematical models account for significant system dynamics such as predator-prey relationships and non-linear growth rates, they generally overlook spatial and temporal heterogeneity in environmental conditions, such as temperature, and population diversity. Future mathematical models will need to incorporate these factors to enhance our understanding of FLA-bacteria dynamics and to provide valuable insights for future risk assessment and disease control measures.