Distinct Cis-acting Elements Combinatorically Mediate Co-localization of mRNAs Encoding for Co-translational Interactors in Cytoplasmic Clusters in S. cerevisiae.

Dynamic functional connectivity brain state dynamics and topological organization in major depressive disorder, anxiety disorder and childhood trauma.

Actin dynamics during contractile ring assembly drives mitotic nuclear displacement in fission yeast.

Combinatorial engineering of 2-C-methyl-D-erythritol 4-phosphate pathway flux optimization and key enzymes spatial organization for (−)-α-bisabolol production in Escherichia coli

Supramolecular engineering of high-efficiency nanozymes via chain-length-directed crystallization of cellulose oligomers.

This study investigates the ecological, spatial, and socio-cultural roles of coastal parks within the urban environments of Kusadasi (Türkiye) and Sumgayit (Azerbaijan), focusing on the comparative analysis of their functional zoning and developmental potential. As coastal cities continue to experience urban expansion and increasing tourism pressure, sustainable strategies for planning, maintaining, and enhancing recreational areas become crucial for ensuring environmental resilience and improving residents’ quality of life. Drawing on landscape-ecological, architectural, and socio-functional perspectives, this research identifies key similarities and differences in the spatial organization, accessibility, and integration of coastal park systems in both cities. Empirical observations and field analyses reveal that Kusadasi’s coastal zone is characterized by its historical heritage and tourism-oriented design, whereas Sumgayit’s boulevard system features a modern, functional layout emphasizing community recreation and urban connectivity. The study highlights the role of coastal parks as regulators of local microclimates, social interaction hubs, and catalysts for sustainable tourism. Based on the comparative assessment, a development concept is proposed that combines Kusadasi’s heritage-sensitive design principles with Sumgayit’s integrated ecological planning approach. The findings underscore the necessity of participatory and inclusive design, improved accessibility, and functional diversity to enhance the adaptive capacity of coastal cities facing climate, demographic, and infrastructural challenges. Ultimately, the research contributes to the discourse on sustainable coastal urbanism by offering a model for harmonizing cultural identity, environmental stewardship, and recreational functionality in coastal park development.

This study aims to identify and analyze the causes of physical deterioration in traditional Ottoman houses located in the urban conservation area of Kula, a district in Manisa, Turkey. These houses, representing a regional interpretation of Ottoman residential architecture, are culturally significant for their unique spatial organization, material use, and ornamental elements. Over time, however, they have suffered severe degradation due to natural, environmental, and anthropogenic factors. Within the scope of the study, 32 structures across six neighborhoods were selected through random sampling, and on-site investigations, facade surveys, and material analyses were conducted. Deterioration was classified into three main categories: material-based (e.g., plaster peeling, decay, corrosion), structural (e.g., collapse, cracking, sagging), and other types (e.g., improper repairs, incongruent additions). Abandoned or underused buildings displayed a significantly higher degree of deterioration compared to those in regular use. The most prominent causes of deterioration were linked to climatic exposure, inadequate maintenance, low-quality materials, and unsympathetic interventions. The findings underscore the necessity for a holistic conservation approach beyond mere building-scale interventions. Strategies such as traditional repair techniques, adaptive reuse, and community engagement are essential for sustainable preservation. This study not only contributes to heritage management in Kula but also offers transferable insights for safeguarding similar vernacular settlements.

ABSTRACT Vascular tissues transport water and nutrients in plants, with the phloem distributing photosynthates from source to sink. The direction of phloem transport is determined by the positional relationship between sources and sinks and by vascular connections. Although aspects of phloem transport have been studied, a comprehensive understanding remains lacking. Here, we used soybean as a model system to investigate the translocation pathways and destinations of photosynthates using autoradiography with ¹⁴C-labeled sucrose and fluorescent imaging with carboxyfluorescein (CF), a known phloem tracer. Soybean exhibits simple phyllotaxy, with alternate trifoliate leaves arranged oppositely along the stem. Applying ¹⁴C-sucrose to mature leaves revealed that young developing leaves received photosynthates from source leaves on both sides of the stem. To visualize pathways, ¹⁴C-sucrose and carboxyfluorescein diacetate (CFDA) were applied to sequential source leaves. Signals from ¹⁴C and CF in the stem's vascular bundles showed no overlap, indicating distinct transport pathways. Additionally, when ¹⁴C-sucrose was applied separately to the left and right halves of a single mature leaf, it was followed corresponding sides to the sink leaves. These findings demonstrate that photosynthates are delivered to sink tissues via multiple, well-compartmentalized phloem pathways, providing new insight into the spatial organization of phloem transport.

This study investigates the usability and user experience of integrating 3D visualizations and short 3D animations into the website interface of a marketing agency. The research evaluates how computer-generated 3D elements influence user interaction, perception, and overall website performance. The experimental phase documents the design process, including software selection, web interface development, and the creation of 3D assets. Target user groups were defined and represented through personas, which informed the specification of website functionality, content structure, and information architecture. Wireframes were designed to determine the spatial organization of interface components, while parallel development focused on producing 3D models and animations intended for web deployment. Usability testing was conducted using the standardized User Experience Questionnaire (UEQ) supplemented with domain-specific questions. Participants interacted with a functional prototype to assess system usability, visual engagement, and navigational efficiency. The findings provide an analysis of user experience outcomes associated with the incorporation of 3D elements into web interfaces. The results offer practical guidance and best-practice recommendations for designers, developers, and content creators seeking to implement 3D visual content as a functional and aesthetic component of modern website design.

The reconstruction of extensive skin defects remains a major challenge in plastic and reconstructive surgery, largely due to the limited vascularization and integration capacity of conventional skin grafts and substitutes. In recent years, three-dimensional bioprinting has emerged as a promising biofabrication strategy capable of addressing these limitations through precise spatial organization of cells, biomaterials, and vascular architectures. This review analyzes current advances in the bioprinting of vascularized skin grafts, with particular emphasis on vascularization strategies, cellular composition, bioink selection, and features relevant to translational application. The findings indicate a clear trend toward hybrid vascularization approaches that combine predefined architectural guidance with endothelial cell–driven self-organization, enabling improved perfusion and viability in thicker constructs. Tri-cellular configurations incorporating keratinocytes, fibroblasts, and endothelial cells are most frequently reported, reflecting efforts to recreate essential skin–vascular interactions. Material strategies increasingly favor decellularized extracellular matrix–based and hybrid bioinks to balance biological fidelity with mechanical stability. Although significant progress has been made toward functional and perfusable skin constructs, challenges remain regarding surgical handling, long-term vascular stability, and standardized personalization workflows. Overall, vascularized bioprinted skin grafts represent a rapidly evolving platform with strong potential to support personalized reconstruction, bridging experimental biofabrication and future reconstructive practice.

This study explores how the architecture of Iranian caravanserais evolved due to changes in architectural knowledge, techniques, and functional needs. The main goal is to classify and compare the physical and architectural features of caravanserais in central Iran to identify their common and distinctive characteristics. The research addresses one main question: How do physical and metaphysical factors influence the formation of architectural styles?. Using a developmental and applied approach, the study combines inductive, interpretive, historical, and comparative methods. Data were collected through library research and field observations. Key architectural components—such as entrances, vestibules, porches, courtyards, rooms, porticos, stables, and towers—were analyzed in terms of spatial organization and typology. Findings show that caravanserai architecture was shaped by the construction traditions and design systems of its time, following shared frameworks created by skilled architects and coordinated institutions. By comparing architectural features, the research identifies which elements remained consistent and which evolved, offering valuable insights for the conservation and restoration of damaged caravanserais. The study focuses on roadside caravanserais in Isfahan, Qom, Markazi, and Tehran provinces, analyzing 65 examples from various historical periods in Iran’s hot and dry central regions

Ovarian tissue cryopreservation followed by transplantation after cancer remission is a fertility preservation strategy available for certain patient groups, such as pre-pubertal and adolescent girls, as well as adult females requiring urgent gonadotoxic therapy. Quantitative assessment of follicular density in cryopreserved cortical tissue is critical for evaluating tissue quality and estimating its reproductive potential. Conventional analysis, based on manual follicle counts in serial histological sections, is time-consuming, labor-intensive, and prone to variability from uneven follicle distribution and inconsistent tissue orientation. To address these limitations, we developed a high-throughput, automated method combining micro-CT, machine learning, and morphological analysis to quantify oocyte density and other morphological features throughout entire ovarian cortical tissue samples. Three-dimensional segmentation analysis enabled quantification of oocyte density in the samples within the cortical region 1mm below the surface epithelium. Oocytes in pediatric samples were located significantly closer to the surface compared to those in adult tissue, with median distances of 139.4μm and 370.2μm, respectively (P < 0.0001) and exhibited markedly higher local oocyte neighbor counts, with median values of 6 and 2 in pediatric and adult tissues, respectively (P < 0.0001), consistent with higher oocyte density and clustered spatial organization in younger individuals. Simulated histology using every 10th virtual sections -corresponding to 40μm separated histology slices- closely approximated full-volume micro-CT estimates of oocyte density. Analysis based on only five virtual sections aligned with micro-CT data exclusively in pediatric samples with high oocyte density, whereas in adult samples it led to substantial inaccuracies in oocyte density estimation. Micro-CT scanning combined with machine learning analysis represents a novel high-throughput and automated approach for estimating oocyte count in cryopreserved ovarian cortical samples. In addition, three-dimensional analysis offers valuable insights into oocyte localization and spatial distribution within the ovarian cortex, presenting a promising alternative to conventional histology for future clinical and research applications.

The present investigation provides a detailed account of the gross morphology and topographical arrangement of a single late-gestation German Shepherd fetus, recovered following natural death associated with an obstetrical complication. Although most prenatal anatomical studies in dogs emphasize larger sample sizes to generate quantitative data, the meticulous examination of a single, well-preserved specimen offers unique value by enabling highly precise documentation of structural development. This individualized approach facilitates a fine-grained description of external landmarks, proportional body configuration, organ position, and the overall maturation status of major systems during advanced gestational age. Standardized gross dissection techniques were employed to examine external and internal features systematically, and the observations were interpreted in light of existing literature on canine embryology and fetal morphology. The fetus exhibited distinct craniofacial outlines, including a proportionately developed skull, clearly formed eyelids, and well-defined oral and nasal regions. Limb development was complete, with identifiable digital pads, flexion points, and joint demarcation indicating advanced musculoskeletal maturation. Internally, all visceral organs were appropriately enclosed within the thoracic and abdominal cavities, showing expected spatial organization for the gestational stage. The lungs displayed clear lobation patterns, while the heart, liver, kidneys, gastrointestinal tract, and urogenital structures appeared anatomically consistent with established prenatal developmental milestones. The relative positioning of the digestive, respiratory, circulatory, and urinary systems reflected near-term topographical organization, supporting the advanced developmental status of the fetus. This descriptive study, although based on a single specimen, contributes valuable baseline information relevant to veterinary anatomists, obstetricians, clinicians, and comparative morphologists. It also provides a useful reference for interpreting prenatal developmental variations, assessing congenital anomalies, guiding imaging-based fetal evaluation, and enriching anatomical teaching resources. The findings reaffirm the importance of detailed qualitative descriptions in complementing quantitative morphometric research on canine prenatal development.

Intrastrain genetic and phenotypic heterogeneity of Pseudomonas aeruginosa is a hallmark of chronic lung infections in individuals with cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD). Although the coexistence of multiple P. aeruginosa lineages within a single host is well documented, the impact of this heterogeneity on infection microbiogeography remains poorly understood. We previously showed that loss of the lipopolysaccharide (LPS) O-specific antigen (OSA) alters P. aeruginosa aggregate assembly. Since OSA-deficient variants are common in chronic pulmonary infections and associated with increased pathogenesis and immune evasion, we investigated whether intrastrain OSA diversity shapes infection microbiogeography. We constructed mixed populations containing equal ratios of OSA-deficient variants and wild-type (WT) cells and examined aggregate assembly and population structures in a synthetic CF sputum model (SCFM2). To assess OSA heterogeneity in vivo, we used a murine pneumonia model combined with hybridization chain reaction (HCR) RNA-FISH and whole-tissue clearing to visualize spatial organization in the airways. In SCFM2, OSA-deficient variants increased total population size, reduced WT aggregate size, and altered spatial organization. We employed 2-plex HCR RNA-FISH to distinguish WT and OSA-deficient variants in murine lungs. Interestingly, in contrast to in vitro conditions, OSA-deficient cells led to significantly larger WT aggregates in the airways. These findings highlight the role of intrastrain genetic heterogeneity in shaping infection microbiogeography and provide a framework for understanding how population dynamics influence microbial physiology and host-pathogen interactions at the micron scale.IMPORTANCEIntrastrain genetic and phenotypic diversity within Pseudomonas aeruginosa populations is common in chronic pulmonary infections. While this intrastrain heterogeneity is a hallmark of chronic infection, its consequences for the spatial organization of P. aeruginosa within the airways remain unclear. Here, we demonstrate that the loss of O-specific antigen in a subpopulation of P. aeruginosa significantly alters the spatial architecture of P. aeruginosa, without changing the total population size or composition. Using a combination of tissue clearing and hybridization chain reaction RNA-FISH in a murine lung infection model, we mapped the localization of genetically distinct P. aeruginosa variants in mixed populations in vivo. These findings reveal that genetic diversification within a strain can reshape the infection landscape at the micron scale, highlighting the overlooked role of intrastrain dynamics in shaping the microbiogeography of infections and influencing host-pathogen interactions.

Mapping the entire transcriptome at single-cell resolution under its natural spatial context is essential for investigating the oncogenesis and progression of diseases. The recently emerged targeted in-situ technologies retain the spatial organization of cells at high resolution, although they remain limited in the number of genes that can be simultaneously measured. To overcome this obstacle, numerous computational methods have been developed to predict unmeasured gene expression in spatial transcriptomics data by leveraging scRNA-seq data. Most of these methods focus on the expression of individual genes and usually generate highly variable predictions. In this study, we introduce PASTA (PAthway-oriented Spatial gene impuTAtion), a spatial pathway expression imputation method that leverages cell type and spatial proximity to enhance prediction accuracy. PASTA assumes that nearby cells and cells of the same type exhibit similar expression patterns, along with pathway information integrated into the imputation process, which improves prediction robustness and enhances biological relevance in spatial transcriptomics data. We demonstrate PASTA's superior performance across both simulated and real-world datasets, highlighting its ability to impute pathway gene expression with improved stability and biological significance.

Reconstructing transcription-translation-coupled DNA replication (TTcDR) in artificial systems is crucial for creating synthetic life; however, existing approaches face limitations mainly due to their reliance on purified biological components. Here, we introduce LoopReX, a cell-free system that reconstitutes TTcDR using crude Escherichia coli extracts, offering a more complex native biological environment. LoopReX leverages a minimal machinery composed of phi29 DNA polymerase and T7 RNA polymerase, with the latter facilitating DNA replication initiation through the generation of primer RNAs. Using machine learning, we optimize LoopReX to enhance the efficiency of both DNA replication and protein expression, achieving scalable, sustainable genetic flow and high-yield protein production with robust iterative performance. Furthermore, artificial nucleoids, autonomously formed through CipB-based compartmentalization, improve DNA spatial organization and support multiple biological functions. This work advances the construction of artificial life by reconstituting TTcDR within a single, scalable, and functionalized system, opening exciting possibilities for synthetic biology, biotechnology, and bio-hybrid applications.

A central question in developmental biology is how embryonic cells acquire and store positional information during pattern formation. In vertebrates, this process begins with the localized activation of signaling systems that mediate axial specification. How these spatial cues are recorded within the regulatory landscape of cells has remained unclear. Here, we report that the chromatin landscape of embryonic cells is spatially patterned during gastrulation. Using spatially resolved genomic analysis in avian embryos, we observed that the epigenome becomes organized in gradients of accessibility and activity along the embryonic axes. These chromatin gradients are established within the loci of developmental genes at the onset of gastrulation and can be used to infer the position of cells in the embryo. Our results show that axial specification involves the spatial organization of the epigenome, linking patterns of chromatin activity to the emergence of the embryonic body plan.

While advances in single-cell genomics have helped to chart the cellular components of tumor ecosystems, it has been more challenging to characterize their specific spatial organization and functional interactions. Here, we combine single-cell RNA-seq, spatial transcriptomics by Slide-seq, and in situ multiplex RNA analysis to create a detailed spatial map of healthy and dysplastic colon cellular ecosystems and their association with disease progression. We profiled inducible genetic CRC mouse models that recapitulate key features of human CRC, assigned cell types and epithelial expression programs to spatial tissue locations in tumors, and computationally used them to identify the regional features spanning different cells in the same spatial niche. We find that tumors were organized in cellular neighborhoods, each with a distinct composition of cell subtypes, expression programs, and local cellular interactions. Comparing to scRNA-seq and bulk RNA-seq data from human CRC, we find that both cell composition and layout features were conserved between the species, with mouse neighborhoods correlating with malignancy and clinical outcome in human patient tumors, highlighting the relevance of our findings to human disease. Our work offers a comprehensive framework that is applicable across various tissues, tumors, and disease conditions, with tools for the extrapolation of findings from experimental mouse models to human diseases.

IntroductionGene expression analysis is crucial for understanding cell identity and function. While single-cell RNA sequencing (scRNA-seq) successfully unveiled cellular heterogeneity, it critically loses the spatial context where cells reside and interact. To address this, spatial transcriptomics (ST) techniques have emerged. Among these, fluorescence in situ hybridization (FISH) based methods have garnered significant attention for their ability to quantify hundreds of genes with subcellular resolution. These methods generate rich transcript point cloud data that incorporates both spatial coordinates and gene identity.A fundamental challenge in ST analysis is to assign each transcript to its corresponding cell to construct accurate cell-level gene expression profiles. Conventional methods often rely on the segmentation of stained images of the nuclei and membrane. However, these image-based approaches suffer from major limitations: low image quality, the need for labor intensive staining, and poor performance in densely packed or noisy tissue regions. Therefore, there is a need for a robust method that can estimate cell properties directly from transcript data without depending on image morphology.In this study, we propose a method to estimate the positions and types of individual cells directly from transcript point clouds. Unlike conventional approaches, our method requires no auxiliary imaging and aims to provide reliable cell-level assignments in noisy or densely packed tissues.Proposed methodOur method estimates the locations and types of individual cells directly from the input transcript point cloud data, where each point is defined by its two-dimensional spatial coordinates and gene identity. Our approach relies on two important properties of tissue organization: tissues are hierarchically structured from cell types down to individual cells, and each cell type is characterized by a distinctive gene expression signature. Cells of the same type therefore form spatially coherent domains that can be distinguished by their expression profiles.The approach consists of two steps. First, we partition the tissue space into hierarchical regions using a quadtree [1] to approximate coarse cell-type-specific domains. This enables the identification of transcript subsets likely belonging to a given type. Second, within each subset, we apply a probabilistic mixture model to identify individual cells. Each component is modeled by a two-dimensional Gaussian distribution for spatial positions and a categorical distribution for gene identities. The parameters and transcript assignments are estimated using an Expectation–Maximization (EM) algorithm. An overview of the proposed method is shown in Fig. 1 (a).To distinguish cell types, our method requires reference data showing the gene expression pattern of each cell type, for example, annotated scRNA-seq data. The output is an assignment of transcripts to unique cell IDs and cell type labels. By directly leveraging spatial and gene expression signatures, our method eliminates the need for auxiliary images, ensuring effectiveness in noisy or densely packed tissues.ExperimentWe evaluated our method on a human lung cancer dataset acquired with the Xenium platform [2]. Annotated scRNA-seq data [3] covering multiple cell types was used as reference data. As a baseline, we compared against the image-based segmentation provided by the Xenium Onboard Analysis pipeline [4].Our results are shown in Fig. 1 (b) and (c), where hierarchical partitioning and clustering were used to define transcript assignments and cell regions. Furthermore, as illustrated in Fig. 2 (a), image-based segmentation failed to recognize cells in certain regions because of weak or ambiguous staining. In contrast, our method was able to reliably detect the cells in these regions (Fig. 2 (b), (c)). This confirms that our approach can robustly identify cells by leveraging transcript distributions alone.Quantitatively, our method achieved a significantly higher transcript-to-cell assignment rate of 0.9996, compared to 0.7891 achieved by the Xenium segmentation. This substantial difference indicates that our method drastically reduces the number of unassigned transcripts and missed cells, providing a more complete profile of tissue heterogeneity. To assess the consistency of the identified cell boundaries, we treated both our unique cell assignments and the image-based segments as cell-level clustering. Their agreement yielded an Adjusted Rand Index (ARI) of 0.4653 and a Normalized Mutual Information (NMI) of 0.8939. These metrics show that our image-free method achieves a comparable level of agreement with the conventional image-based segmentation, while operating solely on transcript data.Overall, the results demonstrate that our method achieves a substantially higher transcript assignment rate and comparable segmentation quality to image-based methods, confirming its robustness and potential as an effective, image-free alternative for cell identification in spatial transcriptomics.DiscussionOur study demonstrates the feasibility of estimating cell positions and types solely from transcript point clouds. By combining spatial organization with characteristic expression profiles, the method enables reliable transcript-to-cell assignment without auxiliary imaging. Applied to lung cancer data, it achieved a higher transcript assignment rate and strong agreement with image-based segmentation, while also detecting cells and transcripts missed by conventional methods. Future directions include scaling the model to larger datasets, validating it across diverse tissue types, and automating processes such as parameter tuning.

The physical learning environment in early childhood education plays a central role in shaping children’s learning experiences, social interactions, and cognitive development. Grounded in the Reggio Emilia concept of the environment as the “third teacher,” this article presents a systematic review of empirical studies examining how physical learning environments support the development of critical thinking and problem-solving skills in early childhood. Using the PRISMA-guided Systematic Literature Review approach, 223 initial records published between 2015 and 2025 were screened, resulting in 20 empirical studies that met inclusion criteria, consisting of 15 empirical articles and 5 essential theoretical or methodological articles. Thematic synthesis generated four major themes: spatial organization that promotes autonomy and collaboration; open-ended materials that stimulate exploration and representational thinking; indoor–outdoor continuity that provides authentic reasoning contexts; and teacher mediation that transforms environmental affordances into meaningful cognitive engagement. Findings indicate that well-designed learning environments that are comfortable, aesthetically rich, and creatively arranged enhance children’s motivation, inquiry behaviors, reasoning skills, and ability to solve problems. This review highlights practical implications for teachers, curriculum designers, and school administrators in optimizing the learning environment to foster higher-order thinking in early childhood education