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Light availability (LAv) dictates a variety of biological and ecological processes across a range of spatiotemporal scales. Quantifying the spatial pattern of LAv in three‐dimensional (3D) space can promote the understanding of microclimates that are critical to fine‐scale species distribution. However, there is still a lack of tools that are robust to evaluate spatiotemporal heterogeneity of LAv in forests. Here, we propose the Forest Light Analyzer python package (FLApy), an open‐source computational tool designed for the analysis of intra‐forest LAv variation across multiple spatial scales. FLApy is freely invoked by Python, facilitating the processing of LiDAR point cloud data into a 3D data container constructed by voxels, as well as traversal calculations related to the LAv regime by high performance synthetic hemispherical algorithm. Furthermore, FLApy incorporates 37 indicators, enabling users to expediently export and visualize LAv patterns and the evaluation of heterogeneity of LAv at two scales (voxel scale and 3D‐cluster scale) for a range of fine‐scale ecological study purposes. To validate the efficacy of the FLApy, we employed a simulated point cloud dataset that simulates forests (varying in canopy closure). Furthermore, to evaluate real world forest, we executed the standard workflow of FLApy utilizing drone‐derived data from three subtropical evergreen broad‐leaved forest dynamics plots within the Ailao Mountain Reserve. Our findings underscore that a series of indices derived from FLApy provide a robust characterization of light availability heterogeneity within diverse forest settings. Additionally, when juxtaposed with conventional monitoring techniques, the metrics offered by FLApy demonstrated better generality in our field assessments. FLApy offers ecologists a solution for rapid quantification of understory light 3D‐regimes across multiple scales, addressing the disparity between traditional manual approaches and the precision required for contemporary ecological studies. Moreover, FLApy provides robust support for the establishment and expansion of heterogeneity indices based on 3D micro‐environments, enhancing our understanding of the largely uncharted 3D structural patterns. Anticipated outcomes suggest that FLApy will enhance our knowledge concerning the intra‐forest climatic conditions into a 3D context, proving pivotal in the delineation of microhabitats and the development of detailed 3D‐scale species distribution models.

Analysis of the in situ stress orientation and magnitude in the No. 4 Structure of Nanpu Sag was performed on the basis of data obtained from borehole breakout and acoustic emission measurements. On the basis of mechanical experiments, logging interpretation, and seismic data, a 3D geological model and heterogeneous rock mechanics field of the reservoir were constructed. Finite element simulation techniques were then used for the detailed prediction of the 3D stress field. The results indicated that the maximum horizontal stress orientation in the study area was generally NEE–SWW trending, with significant changes in the in situ stress orientation within and between fault blocks. Along surfaces and profiles, stress magnitudes were discrete and the in situ stress belonged to the Ia-type. Observed inter-strata differences were characterized as five different types of in situ stress profile. Faults were the most important factor causing large distributional differences in the stress field of reservoirs within the complex fault blocks. The next important influence on the stress field was the reservoir’s rock mechanics parameters, which impacted on the magnitudes of in situ stress magnitudes. This technique provided a theoretical basis for more efficient exploration and development of low-permeability reservoirs within complex fault blocks.

BiofIlm models are commonly used as simulation tools in engineering applications and as research tools to identify and fill gaps in our knowledge of biofilm processes. While models used in engineering applications rely on simplifying assumptions to make them practical, recent experimental evidence of biofilm heterogeneity questions the validity of these assumptions. On the other hand, research models are becoming more complex and use advanced computational tools to mathematically investigate which factors determine the structural heterogeneity and the population dynamics of biofilms. One of the goals of advanced models is to evaluate the relevance of three-dimensional heterogeneities to the predictive capability of traditional biofilm models. In addition, biofilm models are used to evaluate experimental observations when studying a diversity of biofilm-related phenomena. Given the variety of applications of biofilm models and the different approaches that modelers have taken in recent years, a specialist group was convened to evaluate the present status and determine future directions of biofilm modeling research. The education of scientists and engineers on the fundamentals of biofihn models, the development of mathematical models for real-time control of biofilm processes, and the ability to “engineer” the biofilm structure and function (or performance) were identified as the most important objectives for the practical application of biofilm models. As mathematical research tools, biofilm models are directed towards gaining a better understanding of biofilm structure and population dynamics. Specific topics identified as priorities on bioflm research include the behavior of specialist microorganisms, the elucidation of attachment and detachment mechanisms, the determination of mechanical properties of exopolymenc substances, and the study of ecological interactions among different microorganisms. The need to evaluate parameter sensitivity in the different models was identified as an essential component of modeling research. A group decision from this meeting was to initiate a collaborative effort to identify similarities and differences among current modeling approaches. Such comparative analysis will enhance our understanding of biofilm processes and mathematical approaches, and will facilitate the future use of biofilm models by scientists and engineers involved in biofilm research.

Bioprinted breast tumor microenvironment (TME) models with spatial heterogeneity recaptured a well-defined cancer cell-rich stroma structure.Heterogeneity in angiogenesis and extracellular matrix (ECM) stiffness was found in bioprinted TME models.Intercellular crosstalk was identified in bioprinted TME models, which was associated with tumor angiogenesis and ECM remodeling.Bioprinted TME models demonstrated spatially heterogeneous drug resistance in breast cancer. Cellular, extracellular matrix (ECM), and spatial heterogeneity of tumor microenvironments (TMEs) regulate disease progression and treatment efficacy. Developing in vitro models that recapitulate the TME promises to accelerate studies of tumor biology and identify new targets for therapy. Here, we used extrusion-based, multi-nozzle 3D bioprinting to spatially pattern triple-negative MDA-MB-231 breast cancer cells, endothelial cells (ECs), and human mammary cancer-associated fibroblasts (HMCAFs) with biomimetic ECM inks. Bioprinted models captured key features of the spatial architecture of human breast tumors, including varying-sized dense regions of cancer cells and surrounding microvessel-rich stroma. Angiogenesis and ECM stiffening occurred in the stromal area but not the cancer cell-rich (CCR) regions, mimicking pathological changes in patient samples. Transcriptomic analyses revealed upregulation of angiogenesis-related and ECM remodeling-related signatures in the stroma region and identified potential ligand–receptor (LR) mediators of these processes. Breast cancer cells in distinct parts of the bioprinted TME showed differing sensitivities to chemotherapy, highlighting environmentally mediated drug resistance. In summary, our 3D-bioprinted tumor model will act as a platform to discover integrated functions of the TME in cancer biology and therapy. Graphical abstract [Display omitted] This study demonstrates a proof of concept for an in vitro 3D-bioprinted tumor model that recapitulates the spatial heterogeneity of the breast tumor microenvironment. The model mimics key physiological features of patient samples, such as localized vasculature and mechanical stiffness variations, and identifies potential intercellular interactions involved in pathological processes, validating its biological relevance. It also exhibits spatially distinct chemotherapeutic sensitivities, highlighting its potential for studying microenvironment-mediated drug resistance and discovering novel therapies. To advance this technology, optimizing and standardizing the bioprinting process are essential for reproducibility and scalability. Functional assays and preclinical testing are required to validate predictive accuracy. Collaboration with clinical researchers and regulatory bodies is crucial for validation and scale-up, enhancing cancer research and improving therapeutic strategies. Applied bioprinted vascularized breast tumor models recapturing tumor–stroma structures of human breast tumors to study intratumoral heterogeneity and drug resistance. Bioprinted tumor models recapitulated spatially distinct pathological features and identified potential intercellular interactions regulating these pathological changes. Bioprinted tumor models also demonstrated microenvironmentally mediated drug resistance.

ContextThe building landscape greatly affects the urban heat island (UHI), especially in three-dimensional (3D) space, by changing the energy flow between the land surface, the building surface and the lower atmosphere.ObjectivesThis study quantitatively analyzed the relationship between the 3D spatial pattern of buildings and UHI in China’s 30 provincial capitals/municipalities and discussed them at grid-cell scale and city scale, respectively.MethodsIn consideration of the spatial heterogeneity of the urban environment, Geographically Weighted Regression Model (GWR) was selected to identify the effects of 3D building landscape pattern on summer UHI among 30 megacities of China at both micro grid-cell scale and macro city scale. Nine landscape metrics that used to describe the 3D structure of buildings and the UHI that calculated by hot-spot analysis were collected as input variables.ResultsThe floor area ratio (FAR), the average height (AH), and the space congestion degree (SCD) are the most influential factors affecting UHI. AH and SCD are negatively correlated with UHI, while FAR is the opposite. However, these relationships are not static, and they will change when interfered with other factors. The relationship between FAR and UHI becomes negative in the case of relatively low FAR value. In areas with low building coverage ratio, AH is positively correlated with UHI.ConclusionsThe results of this study revealed the complicated association between the 3D building spatial pattern and UHI at micro and macro urban contexts, which was significant for decision-makers to formulate policies based on local conditions.

Newly introduced provisional crowns and fixed dental prostheses (FDP) materials should exhibit good physical and mechanical properties necessary to serve the purpose of their fabrication. The aim of this systematic literature review and meta-analysis is to evaluate the articles comparing the physical and mechanical properties of 3D-printed provisional crown and FDP resin materials with CAD/CAM (Computer-Aided Designing/Computer-Aided Manufacturing) milled and conventional provisional resins. Indexed English literature up to April 2022 was systematically searched for articles using the following electronic databases: MEDLINE-PubMed, Web of Science (core collection), Scopus, and the Cochrane library. This systematic review was structured based on the guidelines given by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The focused PICO/PECO (Participant, Intervention/exposure, Comparison, Outcome) question was: ‘Do 3D-printed (P) provisional crowns and FDPs (I) have similar physical and mechanical properties (O) when compared to CAD/CAM milled and other conventionally fabricated ones (C)’. Out of eight hundred and ninety-six titles, which were recognized after a primary search, twenty-five articles were included in the qualitative analysis, and their quality analysis was performed using the modified CONSORT scale. Due to the heterogeneity of the studies, only twelve articles were included for quantitative analysis. Within the limitations of this study, it can be concluded that 3D-printed provisional crown and FDP resin materials have superior mechanical properties but inferior physical properties compared to CAD/CAM milled and other conventionally fabricated ones. Three-dimensionally printed provisional crowns and FDP materials can be used as an alternative to conventional and CAD/CAM milled long-term provisional materials.

The spatial heterogeneity of aquifer properties plays an important role in the movement of groundwater and contaminants. The characterization of heterogeneity from field observations is often needed to develop groundwater models used to inform management decisions. This research presents a new stochastic facies‐modeling algorithm to represent the heterogeneous deltaic sediments deposits of the Lower Burdekin Delta (LBD) (Australia). The method involves an open‐source, fit‐for‐purpose data and knowledge‐driven approach to improve the heterogeneous representation and spatial modeling of the aquifer. Lithological summary statistics are extracted from legacy boreholes to calibrate the algorithm parameters. The resulting calibrated algorithm generates models that reproduce global facies proportions and global cumulative distribution functions of facies thicknesses. The stochastic simulation of sediment distributions is expected to provide novel inputs to groundwater models of the LBD, which are needed to assess the movement of various solutes, including seawater intrusion, within this important aquifer system.

Hydrogels, being hydrophilic polymer networks capable of absorbing and retaining aqueous fluids, hold significant promise in biomedical applications owing to their high water content, permeability, and structural similarity to the extracellular matrix. Recent chemical advancements have bolstered their versatility, facilitating the integration of the molecules guiding cellular activities and enabling their controlled activation under time constraints. However, conventional synthetic hydrogels suffer from inherent weaknesses such as heterogeneity and network imperfections, which adversely affect their mechanical properties, diffusion rates, and biological activity. In response to these challenges, hybrid hydrogels have emerged, aiming to enhance their strength, drug release efficiency, and therapeutic effectiveness. These hybrid hydrogels, featuring improved formulations, are tailored for controlled drug release and tissue regeneration across both soft and hard tissues. The scientific community has increasingly recognized the versatile characteristics of hybrid hydrogels, particularly in the biomedical sector. This comprehensive review delves into recent advancements in hybrid hydrogel systems, covering the diverse types, modification strategies, and the integration of nano/microstructures. The discussion includes innovative fabrication techniques such as click reactions, 3D printing, and photopatterning alongside the elucidation of the release mechanisms of bioactive molecules. By addressing challenges, the review underscores diverse biomedical applications and envisages a promising future for hybrid hydrogels across various domains in the biomedical field.

Cell migration through 3D extracellular matrices is critical to the normal development of tissues and organs and in disease processes, yet adequate analytical tools to characterize 3D migration are lacking. Here, we quantified the migration patterns of individual fibrosarcoma cells on 2D substrates and in 3D collagen matrices and found that 3D migration does not follow a random walk. Both 2D and 3D migration features a non-Gaussian, exponential mean cell velocity distribution, which we show is primarily a result of cell-to-cell variations. Unlike in the 2D case, 3D cell migration is anisotropic: velocity profiles display different speed and self-correlation processes in different directions, rendering the classical persistent random walk (PRW) model of cell migration inadequate. By incorporating cell heterogeneity and local anisotropy to the PRW model, we predict 3D cell motility over a wide range of matrix densities, which identifies density-independent emerging migratory properties. This analysis also reveals the unexpected robust relation between cell speed and persistence of migration over a wide range of matrix densities.

We have studied the three-dimensional (3D) cytoarchitecture of the human hippocampus in neuropathologically healthy and Alzheimer’s disease (AD) individuals, based on phase-contrast X-ray computed tomography of postmortem human tissue punch biopsies. In view of recent findings suggesting a nuclear origin of AD, we target in particular the nuclear structure of the dentate gyrus (DG) granule cells. Tissue samples of 20 individuals were scanned and evaluated using a highly automated approach of measurement and analysis, combining multiscale recordings, optimized phase retrieval, segmentation by machine learning, representation of structural properties in a feature space, and classification based on the theory of optimal transport. Accordingly, we find that the prototypical transformation between a structure representing healthy granule cells and the pathological state involves a decrease in the volume of granule cell nuclei, as well as an increase in the electron density and its spatial heterogeneity. The latter can be explained by a higher ratio of heterochromatin to euchromatin. Similarly, many other structural properties can be derived from the data, reflecting both the natural polydispersity of the hippocampal cytoarchitecture between different individuals in the physiological context and the structural effects associated with AD pathology.