Spatial Proximity Research Articles

The N-terminal activation function AF-1 domain of ERα interacts directly with the C-terminal AF-2-holding ligand-binding domain to recruit the coactivator proteins.

Cryoelectron microscopy (cryo-EM) clarified the quaternary structure of the DNA complex of coactivator-bound estrogen receptor alpha (ERα), revealing the adjacency of the N-terminal domain (NTD) and C-terminal ligand-binding domain (LBD). ERα-NTD and LBD constitute activation function 1 (AF-1) and activation function 2 (AF-2), respectively. These domains are essential for transcription activation. Their spatial proximity was judged to be essential for ERα to recruit the SRC coactivator proteins. In the present study, we first evaluated untethered free ERα-NTD(AF-1) [residues 1-180] and its-truncated desNTD(AF-1)-ERα [residues 181-595] in a luciferase reporter gene assay. ERα-NTD(AF-1) was completely inactive, whereas desNTD(AF-1)-ERα exhibited 66% activity of wild-type ERα. Surprisingly, ERα-NTD(AF-1) was found to inhibit desNTD(AF-1)-ERα markedly. Therefore, assuming that ERα-NTD(AF-1) must also inhibit wild-type full-length ERα, we co-expressed ERα-NTD(AF-1) and full-length ERα. As expected, ERα-NTD(AF-1) inhibited ERα in a dose-dependent manner, but non-competitively for 17β-estradiol. When their intracellular transport was examined immunocytochemically, ERα-NTD(AF-1) showed a distinct translocation from the cytoplasm to the nucleus, despite being expressed solely in the cytoplasm without full-length ERα. This nuclear translocation was attributable to a direct interaction between ERα-NTD(AF-1) and full-length ERα consisting of the nuclear localization signal. The present results demonstrated that, in full-length ERα, the N-terminally tethered NTD(AF-1) domain collaborates with the C-terminal LBD(AF-2) for coactivator recruitment.

Graph attention automatic encoder based on contrastive learning for domain recognition of spatial transcriptomics

Spatial transcriptomics is an emerging technology that enables the profiling of gene expression in tissues while preserving spatial location information. This innovative approach is anticipated to provide a comprehensive understanding of the spatial distribution of different cells within tissues and facilitate in-depth analysis of tissue structure. To accurately recognize spatial domains from spatial transcriptomics, we have introduced a generalized deep learning method called GAAEST (Graph Attention-based Autoencoder for Spatial Transcriptomics). Our proposed approach effectively integrates both spatial location information and gene expression data from spatial transcriptomics. Specifically, it leverages spatial location details to construct a neighborhood graph and employs a graph attention network-based encoder to embed gene expression information into a spatially informed space. At the same time, to further optimize the learned potential embedding, self-supervised contrastive learning is introduced to capture spatial information at three levels: local, global and contextual feature of spots. Finally, the decoder reconstructs gene expressions, which are then clustered to identify spatial domains with similar expression patterns and spatial proximity. Based on our experiments conducted on multiple datasets, GAAEST consistently outperforms existing state-of-the-art methods. The proposed GAAEST demonstrates excellent capabilities in spatial domain recognition, positioning it as an ideal tool for advancing spatial transcriptomics research.

Follow which leader? Spatial mimicry and broad‐based equity‐ and profit‐sharing plans

AbstractOrganizations have both local and nationally prominent peers from which they can model their human resource management practices. How does a focal organization reconcile the influence of smaller, spatially proximate peer organizations with the influence of prominent, distant organizations? We develop the concept of spatial mimetic gravity to estimate the mimetic pressures a focal organization feels from its geographically proximate and distant peers. We examine the population of craft beer brewers in the United States between 2013 and 2019 and find that the propensity to offer a stock ownership or profit‐sharing plan is a function of a focal brewery's spatial proximity to its peers and their prominence. We help explain why some firms offer broad‐based equity‐sharing and profit‐sharing plans and others do not. In doing so, we argue that organizational spatial mimicry is best understood from a gravity approach, adding a field‐level explanation to previously individually focused theory about organizational choices.

HiCDiffusion - diffusion-enhanced, transformer-based prediction of chromatin interactions from DNA sequences

Prediction of chromatin interactions from DNA sequence has been a significant research challenge in the last couple of years. Several solutions have been proposed, most of which are based on encoder-decoder architecture, where 1D sequence is convoluted, encoded into the latent representation, and then decoded using 2D convolutions into the Hi-C pairwise chromatin spatial proximity matrix. Those methods, while obtaining high correlation scores and improved metrics, produce Hi-C matrices that are artificial - they are blurred due to the deep learning model architecture. In our study, we propose the HiCDiffusion, sequence-only model that addresses this problem. We first train the encoder-decoder neural network and then use it as a component of the diffusion model - where we guide the diffusion using a latent representation of the sequence, as well as the final output from the encoder-decoder. That way, we obtain the high-resolution Hi-C matrices that not only better resemble the experimental results - improving the Fréchet inception distance by an average of 11 times, with the highest improvement of 56 times - but also obtain similar classic metrics to current state-of-the-art encoder-decoder architectures used for the task.

Pre-Detection and Pre-Registration Averaging of Full Wave Signals in Airborne LiDAR Bathymetry

A well-known technique to enhance the signal to noise ratio (SNR) of repetitive signals is to average them. The coherent parts of the signal add up constructively while the incoherent parts are averaged out. The prerequisite is that the signals are acquired under conditions of high repeatability, i.e., the signals must be sufficiently similar. In the present technical note, we describe an efficient method for maintaining signal similarity by ensuring spatial and temporal proximity of laser waveform signals obtained by a sensor operated from an airborne platform. The method makes use of a few auxiliary parameters such as laser pulse repetition rate, mirror rotation rate, platform altitude and flight speed. The method can be extended to be operated in real time.

Nuclear compensatory evolution driven by mito-nuclear incompatibilities

Mitochondrial function relies on the coordinated expression of mitochondrial and nuclear genes, exhibiting remarkable resilience despite high mitochondrial mutation rates. The nuclear compensation mechanism suggests deleterious mitochondrial alleles drive compensatory nuclear mutations to preserve mito-nuclear compatibility. However, prevalence and factors conditioning this phenomenon remain debated due to its conflicting evidence. Here, we investigate how mito-nuclear incompatibilities impact substitutions in a model for species radiation. Mating success depends on genetic compatibility (nuclear DNA) and spatial proximity. Populations evolve from partially compatible mito-nuclear states, simulating mitochondrial DNA (mtDNA) introgression. Mutations do not confer advantages nor disadvantages, but individual fecundity declines with increasing incompatibilities, selecting for mito-nuclear coordination. We find that selection for mito-nuclear compatibility affects each genome differently based on their initial state. In compatible gene pairs, selection reduces substitutions in both genomes, while in incompatible nuclear genes, it consistently promotes compensation, facilitated by more mismatches. Interestingly, high mitochondrial mutation rates can reduce nuclear compensation by increasing mtDNA rectification, while substitutions in initially compatible nuclear gene are boosted. Finally, the presence of incompatibilities accelerates species radiation, but equilibrium richness is not directly correlated to substitution rates, revealing the complex dynamics triggered by mitochondrial introgression and mito-nuclear coevolution. Our study provides a perspective on nuclear compensation and the role of mito-nuclear incompatibilities in speciation by exploring extreme scenarios and identifying trends that empirical data alone cannot reveal. We emphasize the challenges in detecting these dynamics and propose analyzing specific genomic signatures could shed light on this evolutionary process.

Spatially Informed Graph Structure Learning Extracts Insights from Spatial Transcriptomics.

Embeddings derived from cell graphs hold significant potential for exploring spatial transcriptomics (ST) datasets. Nevertheless, existing methodologies rely on a graph structure defined by spatial proximity, which inadequately represents the diversity inherent in cell-cell interactions (CCIs). This study introduces STAGUE, an innovative framework that concurrently learns a cell graph structure and a low-dimensional embedding from ST data. STAGUE employs graph structure learning to parameterize and refine a cell graph adjacency matrix, enabling the generation of learnable graph views for effective contrastive learning. The derived embeddings and cell graph improve spatial clustering accuracy and facilitate the discovery of novel CCIs. Experimental benchmarks across 86 real and simulated ST datasets show that STAGUE outperforms 15 comparison methods in clustering performance. Additionally, STAGUE delineates the heterogeneity in human breast cancer tissues, revealing the activation of epithelial-to-mesenchymal transition and PI3K/AKT signaling in specific sub-regions. Furthermore, STAGUE identifies CCIs with greater alignment to established biological knowledge than those ascertained by existing graph autoencoder-based methods. STAGUE also reveals the regulatory genes that participate in these CCIs, including those enriched in neuropeptide signaling and receptor tyrosine kinase signaling pathways, thereby providing insights into the underlying biologicalprocesses.

Offspring may succeed well next to their relatives, but it needs particular traits.

There is ongoing debate about whether offspring perform best next to phylogenetically distantly related adult neighbours (due to the scarcity of enemies and competitors) or next to closely related adults (due to the abundance of mutualists). Here we hypothesise that relatedness of adult neighbours affects which traits confer performance rather than performance itself. We studied seed removal, seed germination and sapling growth in Sessile Oaks (Quercus petraea and hybrids), and how they depend on size, shape and other traits, under both closely and distantly related canopies, manipulating offspring-density, presence of insects, and fungi, and spatial proximity to oaks. We found that phylogenetic distance of adult neighbours affects only little performance of offspring but strongly which traits confer performance to offspring, in particular the size and shape of seeds and saplings. Differences in trait-performance relationships mostly disappear once insects or conspecific competitors are excluded (albeit exclusion of fungi reinforced these differences). Effects of phylogenetic distance of neighbours were not replaceable by the percentage of the gymnosperms among neighbours, nor the environmental conditions considered. We suggest that by responding to a biotic micro-mosaic of selection pressures, Sessile Oak flexibly succeeds in diverse neighbourhoods. Sessile Oak might maintain the potential for both, convergence with and divergence from phylogenetically distantly related species, thereby reinforcing or eroding phylogenetic signal of niches.

Graph-Based Spatial Proximity of Super-Resolved Protein–Protein Interactions Predicts Cancer Drug Responses in Single Cells

Graph-Based Spatial Proximity of Super-Resolved Protein–Protein Interactions Predicts Cancer Drug Responses in Single Cells

Can Spatial Proximity to Another Country Drive Short-distance Transnationalism? Evidence from Social Ties in Three European Border Regions

ABSTRACT This article draws inspiration from social network analysis (SNA) to investigate the impact of spatial proximity on the geography of strong social ties in three European border regions. We consider cross-border friendship and kinship as a measure of short-distance transnationalism, examine the conditions under which the latter is likely to emerge, and systematically compares our findings with “traditional” forms of transnationalism. The study is based on a large-scale and representative quantitative survey (N = 3,215) conducted in the Geneva, Lille, and Basque border regions in order to assess the impact of cross-border integration intensity on the inter-personal relationships of all residents, regardless of their migration experiences. The results indicate that only 11.9% of the residents reported having at least one strong cross-border tie. Binomial regression models are used to demonstrate that cross-border ties are not solely shaped by proximity, but also depend on individuals’ socioeconomics, on their mobility experiences, and on contextual factors. This article shows that cross-border integration primarily fosters cross-border friendships rather than kinships, and that cross-border ties are not evenly distributed among the population. Individuals born in the studied border regions do not have the highest levels of short-distance transnationalism, raising a discussion about the importance of promoting cross-border rootedness.

Single-cell characterization of differentiation trajectories and drug resistance features in gastric cancer with peritoneal metastasis.

Gastric cancer patients with peritoneal metastasis (GCPM) experience a rapidly deteriorating clinical trajectory characterized by therapeutic resistance and dismal survival, particularly following the development of malignant ascites. However, the intricate dynamics within the peritoneal microenvironment (PME) during the treatment process remain largely unknown. Matched samples from primary tumours (PT), peritoneal metastases (PM), and paired pre-treatment and post-chemo/immunotherapy (anti-PD-1/PD-L1) progression malignant ascites samples, were collected from 48 patients. These samples were subjected to single-cell RNA sequencing (n=30), multiplex immunofluorescence (n=30), and spatial transcriptomics (n=3). Furthermore, post hoc analyses of a phase 1 clinical trial (n=20, NCT03710265) and an in-house immunotherapy cohort (n=499) were conducted to validate the findings. Tracing the evolutionary trajectory of epithelial cells unveiled the terminally differentially MUC1+ cancer cells with a high epithelial-to-mesenchymal transition potential, and they demonstrated spatial proximity with fibroblasts and endothelial cells, correlating with poor prognosis. A significant expansion of macrophage infiltrates, which exhibited the highest proangiogenic activity, was observed in the ascites compared with PT and PM. Besides, higher C1Q+ macrophage infiltrates correlated with significantly lower GZMA+ T-lymphocyte infiltrates in therapeutic failure cases, potentially mediated by the LGALS9-CD45 and SPP1-CD44 ligand-receptor interactions. In the chemoresistant group, intimate interactions between C1Q+ macrophages and fibroblasts through the complement activation pathway were found. In the group demonstrating immunoresistance, heightened TGF-β production activity was detected in MUC1+ cancer cells, and they were skewed to interplay with C1Q+ macrophages through the GDF15-TGF-βR2 axis. Ultimately, post hoc analyses indicated that co-targeting TGF-β and PDL1 pathways may confer superior clinical benefits than sole anti-PD-1/PD-L1 therapy for patients presenting with GCPM at the time of diagnosis. Our findings elucidated the cellular differentiation trajectories and crucial drug resistance features within PME, facilitating the exploration of effective targets for GCPM treatment. MUC1+ cancer cells with a high epithelial-to-mesenchymal transition potential and exhibiting spatial proximity to fibroblasts and endothelial cells constitute the driving force of gastric cancer peritoneal metastasis (GCPM). Higher C1Q+ macrophage infiltrates correlated with significantly lower GZMA+ T-lymphocyte infiltrates within the peritoneal microenvironment in therapeutic failure cases. Co-targeting TGF-β and PDL1 pathways may confer superior clinical benefits than sole anti-PD-1/PD-L1 therapy for patients presenting with GCPM at diagnosis.

Exploring language relations through syntactic distances and geographic proximity

Languages are grouped into families that share common linguistic traits. While this approach has been successful in understanding genetic relations between diverse languages, more analyses are needed to accurately quantify their relatedness, especially in less studied linguistic levels such as syntax. Here, we explore linguistic distances using series of parts of speech (POS) extracted from the Universal Dependencies dataset. Within an information-theoretic framework, we show that employing POS trigrams maximizes the possibility of capturing syntactic variations while being at the same time compatible with the amount of available data. Linguistic connections are then established by assessing pairwise distances based on the POS distributions. Intriguingly, our analysis reveals definite clusters that correspond to well known language families and groups, with exceptions explained by distinct morphological typologies. Furthermore, we obtain a significant correlation between language similarity and geographic distance, which underscores the influence of spatial proximity on language kinships.

Cu-TM (Mn, Fe, Ni) dual-atom vs. Pt single atom: TM atoms modulate the electronic structure of Cu sites supported on melamine aerogel to enhance the catalytic purification performance of CH3SH

Despite the high atomic utilization and unique electronic properties of single-atom catalysts (SACs), the single active site to some extent limits the rapid and stable execution of complex reactions involving multiple steps and intermediates on the SACs surface. To address this issue, dual-atom catalysts (DACs) have emerged. The specific spatial proximity enables a synergistic effect between the diatomic pairs, significantly promoting catalytic reactions, though the exact synergistic mechanisms remain to be explored. In this work, we successfully constructed Cu single-atom (Cu-MA) and CuTM (transition metal, TM = Mn, Fe, Ni) dual-atom (CuTM-MA) catalysts on the surface of melamine aerogel (MA) via the impregnation method. Additionally, single-atom catalysts with different Pt loadings (0.5 %, 1 %, and 2 %) (Pt-MA) were synthesized to compare the CH3SH decomposition activity with that of CuTM-MA. Experimental results showed that CuTM-MA significantly outperformed Cu-MA and even rivaled Pt-MA at high temperatures. Utilizing Cu K-edge XAFS, we found that the presence of TM not only enhanced the stability of Cu atoms on the MA surface, preventing aggregation at high temperatures to some extent, but also effectively modulated the electronic structure of Cu atoms, promoting electron transfer from Cu to TM, thus achieving a significant enhancement in catalytic activity.

Near or far? An investigation into the relationship between spatial proximity to CSRC district offices and stock crash risk

ABSTRACT Our analysis reveals that companies with headquarters in further proximity to China Securities Regulatory Commission (CSRC) district offices are more susceptible to stock crash risk. Furthermore, this relationship is notably stronger for firms whose CEOs lack political connections, are non-state-owned, and are not audited by the Big Four audit firms. Our findings imply that regulatory remoteness plays a crucial role in shaping stock market dynamics and risk.

Self-consistent modelling of radio frequency sheath in 3D with realistic ICRF antennas

Abstract Ion Cyclotron Resonant Frequency (ICRF) induced impurity production has raised many concerns since ITER proposed to change the first wall material from beryllium to tungsten. Enhanced DC plasma potential (VDC) due to RF sheath rectification is well known as one of the most important mechanisms behind the RF induced impurities. Our previous work (L. Lu et.al, Plasma Phys. Control. Fusion 60 (2018) 035003) considered the impact of both the slow wave and the fast wave on the RF sheath rectification in a 2D geometry. It can barely recover the double-hump structure of the VDC poloidal distribution observed in various machines when only the slow wave is modelled using the multi-2D approach which intrinsically assumes the poloidal wavenumber kz is zero. The fast wave on the other hand is found to be more sensitive to a finite kz and may need to be tackled in 3D. This work reports our recent progress on the 3D RF sheath modelling. In this new code, the latest RF sheath boundary conditions (J. R. Myra, J. Plasma Phys. 87 (2021) 905870504) and the realistic 3D ICRF antennas are implemented. Compared to the 2D results, the 3D code could well recover the double-hump poloidal distribution of VDC even with the fast wave included, which confirms our speculation on the necessity of treating the fast wave in 3D. While the double-hump pattern is robust in the simulation, the amplitude of VDC is found to be affected by the magnetic tilt angle and the antenna geometry. This emphasizes the importance of adopting a realistic antenna geometry in the RF sheath modelling. The double-hump VDC poloidal structure breaks as the magnetic tilt angle increases. This is explained by the gyrotropic property of the cold plasma dielectric tensor. The spatial proximity effect we identified in the previous 2D simulations is still valid in 3D. Finally, simulation shows the slow wave dominates the RF sheath excitation in the private SOL, while the fast wave gradually takes over when moving to the far SOL region. This code could be a new tool to provide numerical support for ITER impurity assessment and ICRF antenna design.

Spatial multiplexed immunofluorescence analysis reveals coordinated cellular networks associated with overall survival in metastatic osteosarcoma

Patients diagnosed with advanced osteosarcoma, often in the form of lung metastases, have abysmal five-year overall survival rates. The complexity of the osteosarcoma immune tumor microenvironment has been implicated in clinical trial failures of various immunotherapies. The purpose of this exploratory study was to spatially characterize the immune tumor microenvironment of metastatic osteosarcoma lung specimens. Knowledge of the coordinating cellular networks within these tissues could then lead to improved outcomes when utilizing immunotherapy for treatment of this disease. Importantly, various cell types, interactions, and cellular neighborhoods were associated with five-year survival status. Of note, increases in cellular interactions between T lymphocytes, positive for programmed cell death protein 1, and myeloid-derived suppressor cells were observed in the 5-year deceased cohort. Additionally, cellular neighborhood analysis identified an Immune-Cold Parenchyma cellular neighborhood, also associated with worse 5-year survival. Finally, the Osteosarcoma Spatial Score, which approximates effector immune activity in the immune tumor microenvironment through the spatial proximity of immune and tumor cells, was increased within 5-year survivors, suggesting improved effector signaling in this patient cohort. Ultimately, these data represent a robust spatial multiplexed immunofluorescence analysis of the metastatic osteosarcoma immune tumor microenvironment. Various communication networks, and their association with survival, were described. In the future, identification of these networks may suggest the use of specific, combinatory immunotherapeutic strategies for improved anti-tumor immune responses and outcomes in osteosarcoma.

Brilliant tragedy? Electoral effects of environmental protest cycle in autocracy

ABSTRACT When and how does an environmental protest cycle affect election outcomes under electoral authoritarianism? Drawing on the case of the Bashkortostan republic, a Russian ethnic region, I leverage the spatial proximity to the protest site to identify its effects on parliamentary elections. The environmental protest cycle peaked in Bashkortostan around the regional government’s decisions to extract minerals from shikhans – mountains composed of limestone. Employing a difference-in-differences (DiD) design, I show that precincts exposed to the environmental protest cycle experienced a significant drop in United Russia vote share, while voting for systemic opposition increased in the affected precincts. To explain the dynamics, I propose treating non-political protests, such as environmental ones, as an information revelation mechanism. The mechanism identified through a causal mediation analysis indicates that the environmental protest cycle conveys information on regional malperformance to voters. Their updated preferences, in turn, heavily undermine the electoral mobilizing capacity of local elites.

Embodied/Encoded: A Study of Presence in Digital Music

Presence in Embodied/Encoded is concerned with the physical and embodied dimensions of musicking in relation to digital-informational representations of such phenomena. I explore presence through practices of recording, creative coding, audio production, and spatial electronic music composition. Of particular interest is the link between presence and the sensual/corporeal aspects of sound production and listening. Research in embodied music cognition and extended reality provide a foundation for this type of meaning formation. In the context of immersive electronic music, I suggest that physical presence – a sense of ‘being somewhere’—emerges not just from images/representations of place, but from peripheral aspects of the (embodied) acoustic experience such as spatial proximity and distance, diffuseness, resonance and reverberation, noise floor, etc. Consequently, musical meaning in “Embodied/Encoded” moves away from the symbolic dimension of electronic sounds toward meaning as an outcome of embodied interaction with the environment. The concept of presence can also apply to ‘mixed’ music, or combinations of acoustic and electronic sources, in which virtual presence is complicated by real bodies and spaces. Digital technology renders sound a flexible, malleable entity—a ‘flickering’ signifier to borrow from Hayles—capable of reconfiguring presence in creative ways. The dance between encoded and embodied dimensions inspires and informs this artistic research. Through a body of immersive music and multimedia documentation, I unpack connections between presence and its digital abstractions.

Update on a brain-penetrant cardiac glycoside that can lower cellular prion protein levels in human and guinea pig paradigms.

Lowering the levels of the cellular prion protein (PrPC) is widely considered a promising strategy for the treatment of prion diseases. Building on work that established immediate spatial proximity of PrPC and Na+, K+-ATPases (NKAs) in the brain, we recently showed that PrPC levels can be reduced by targeting NKAs with their natural cardiac glycoside (CG) inhibitors. We then introduced C4'-dehydro-oleandrin as a CG with improved pharmacological properties for this indication, showing that it reduced PrPC levels by 84% in immortalized human cells that had been differentiated to acquire neural or astrocytic characteristics. Here we report that our lead compound caused cell surface PrPC levels to drop also in other human cell models, even when the analyses of whole cell lysates suggested otherwise. Because mice are refractory to CGs, we explored guinea pigs as an alternative rodent model for the preclinical evaluation of C4'-dehydro-oleandrin. We found that guinea pig cell lines, primary cells, and brain slices were responsive to our lead compound, albeit it at 30-fold higher concentrations than human cells. Of potential significance for other PrPC lowering approaches, we observed that cells attempted to compensate for the loss of cell surface PrPC levels by increasing the expression of the prion gene, requiring daily administration of C4'-dehydro-oleandrin for a sustained PrPC lowering effect. Regrettably, when administered systemically in vivo, the levels of C4'-dehydro-oleandrin that reached the guinea pig brain remained insufficient for the PrPC lowering effect to manifest. A more suitable preclinical model is still needed to determine if C4'-dehydro-oleandrin can offer a cost-effective complementary strategy for pushing PrPC levels below a threshold required for long-term prion disease survival.

The impact of gunfire on residential property values

ABSTRACT Hedonic studies of housing unit prices routinely attribute lower prices to perceived undesirable attributes and or amenities of the property sold. A steady stream of literature finds that criminal behaviour is negatively capitalized into housing unit prices. This study focuses on the effects of geocoded gunfire incidents on housing unit prices while controlling for other attributes and amenities at the census-block group level. The primary finding is that spatial and temporal proximity of gunfire incidents reduces housing unit prices in an analysis of 3,844 gunfire incidents, involving over 15,000 rounds of gunfire and 2,053 housing unit sales in Savannah, Georgia, from 2015 to 2020. The effect of gunfire is greater when it occurs in the immediate vicinity of the property. Heterogeneous effects on sale prices were found to be present across time and space when intensity was measured by the number of days with gunfire incidents and to a lesser extent when intensity was measured by the number of shots fired in each incident.