Single-Molecule Spectroscopy and Super-Resolution Mapping of Physicochemical Parameters in Living Cells.

By superlocalizing the positions of millions of single molecules over many camera frames, a class of super-resolution fluorescence microscopy methods known as single-molecule localization microscopy (SMLM) has revolutionized how we understand subcellular structures over the past decade. In this review, we highlight emerging studies that transcend the outstanding structural (shape) information offered by SMLM to extract and map physicochemical parameters in living mammalian cells at single-molecule and super-resolution levels. By encoding/decoding high-dimensional information-such as emission and excitation spectra, motion, polarization, fluorescence lifetime, and beyond-for every molecule, and mass accumulating these measurements for millions of molecules, such multidimensional and multifunctional super-resolution approaches open new windows into intracellular architectures and dynamics, as well as their underlying biophysical rules, far beyond the diffraction limit.

Coherent mapping of position and head direction across auditory and visual cortex.

Neurons in primary visual cortex (V1) may not only signal current visual input but also relevant contextual information such as reward expectancy and the subject's spatial position. Such contextual representations need not be restricted to V1 but could participate in a coherent mapping throughout sensory cortices. Here, we show that spiking activity coherently represents a location-specific mapping across auditory cortex (AC) and lateral, secondary visual cortex (V2L) of freely moving rats engaged in a sensory detection task on a figure-8 maze. Single-unit activity of both areas showed extensive similarities in terms of spatial distribution, reliability, and position coding. Importantly, reconstructions of subject position based on spiking activity displayed decoding errors that were correlated between areas. Additionally, we found that head direction, but not locomotor speed or head angular velocity, was an important determinant of activity in AC and V2L. By contrast, variables related to the sensory task cues or to trial correctness and reward were not markedly encoded in AC and V2L. We conclude that sensory cortices participate in coherent, multimodal representations of the subject's sensory-specific location. These may provide a common reference frame for distributed cortical sensory and motor processes and may support crossmodal predictive processing.

Trace element pollution tracking in the complex multi-aquifer groundwater system of Al-Hassa oasis (Saudi Arabia) using spatial, chemometric and index-based techniques.

In a global context, trace element pollution assessment in complex multi-aquifer groundwater systems is important, considering the growing concerns about water resource quality and sustainability worldwide. This research addresses multiple objectives by integrating spatial, chemometric, and indexical study approaches, for assessing trace element pollution in the multi-aquifer groundwater system of the Al-Hassa Oasis, Saudi Arabia. Groundwater sampling and analysis followed standard methods. For this purpose, the research employed internationally recognized protocols for groundwater sampling and analysis, including standardized techniques outlined by regulatory bodies such as the United States Environmental Protection Agency (USEPA) and the World Health Organization (WHO). Average values revealed that Cr (0.041) and Fe (2.312) concentrations surpassed the recommended limits for drinking water quality, posing serious threats to groundwater usability by humans. The trace elemental concentrations were ranked as: Li < Mn < Co < As < Mo < Zn < Al < Ba < Se < V < Ni < Cr < Cu < B < Fe < Sr. Various metal(loid) pollution indices, including degree of contamination, heavy metal evaluation index, heavy metal pollution index, and modified heavy metal index, indicated low levels of groundwater pollution. Similarly, low values of water pollution index and weighted arithmetic water quality index were observed for all groundwater points, signifying excellent groundwater quality for drinking and domestic purposes. Spatial distribution analysis showed diverse groundwater quality across the study area, with the eastern and western parts displaying a less desirable quality, while the northern has the best, making water users in the former more vulnerable to potential pollution effects. Thus, the zonation maps hinted the necessity for groundwater quality enhancement from the western to the northern parts. Chemometric analysis identified both human activities and geogenic factors as contributors to groundwater pollution, with human activities found to have more significant impacts. This research provides the scientific basis and insights for protecting the groundwater system and ensuring efficient water management.

Real-Time Spatial Mapping in Architectural Visualization: A Comparison among Mixed Reality Devices.

Recent advancements in communication technology have catalyzed the widespread adoption of realistic content, with augmented reality (AR) emerging as a pivotal tool for seamlessly integrating virtual elements into real-world environments. In construction, architecture, and urban design, the integration of mixed reality (MR) technology enables rapid interior spatial mapping, providing clients with immersive experiences to envision their desires. The rapid advancement of MR devices, or devices that integrate MR capabilities, offers users numerous opportunities for enhanced entertainment experiences. However, to support designers at a high level of expertise, it is crucial to ensure the accuracy and reliability of the data provided by these devices. This study explored the potential of utilizing spatial mapping within various methodologies for surveying architectural interiors. The objective was to identify optimized spatial mapping procedures and determine the most effective applications for their use. Experiments were conducted to evaluate the interior survey performance, using HoloLens 2, an iPhone 13 Pro for spatial mapping, and photogrammetry. The findings indicate that HoloLens 2 is most suited for the tasks examined in the scope of these experiments. Nonetheless, based on the acquired parameters, the author also proposes approaches to apply the other technologies in specific real-world scenarios.

Novel Techniques for Mapping DNA Damage and Repair in the Brain.

DNA damage in the brain is influenced by endogenous processes and metabolism along with exogenous exposures. Accumulation of DNA damage in the brain can contribute to various neurological disorders, including neurodegenerative diseases and neuropsychiatric disorders. Traditional methods for assessing DNA damage in the brain, such as immunohistochemistry and mass spectrometry, have provided valuable insights but are limited by their inability to map specific DNA adducts and regional distributions within the brain or genome. Recent advancements in DNA damage detection methods offer new opportunities to address these limitations and further our understanding of DNA damage and repair in the brain. Here, we review emerging techniques offering more precise and sensitive ways to detect and quantify DNA lesions in the brain or neural cells. We highlight the advancements and applications of these techniques and discuss their potential for determining the role of DNA damage in neurological disease.

Diffuse reflectance spectroscopy and digital soil mapping for assessing soil-associated off-road vehicle mobility risk.

Soil attributes such as granulometric fractions and Atterberg limits (LL: liquid limit, PL: plastic limit, and PI: plasticity index) are needed to assess off-road vehicle mobility (OVM) risks. Parameters describing these attributes are generally measured in soil samples collected from a few locations through cumbersome laboratory methods. Although diffuse reflectance spectroscopy (DRS) can rapidly yield estimates for soil attributes in samples collected from specific locations and digital soil mapping (DSM) can transform such discrete measurements into spatially-continuous inference systems, these two technologies are rarely used for assessing OVM risks. In this study, we combined the DRS and DSM approaches for deriving spatially-continuous estimates for the key vehicle mobility parameters (gravel, sand, and fine particles; Cu: coefficients of uniformity; Cc: coefficient of curvature; LL; and PI) and classified soils using the Unified Soil Classification System (USCS). A total of 204 soil samples were collected from the north-eastern Himalayan state of Sikkim for measuring these parameters along with spectral reflectance over the visible and near-infrared region. Results of the chemometric models in the DRS approach showed that the USCS parameters may be estimated with the coefficient of determination (R2) values as high as 0.72. The fine (<2 mm diameter) fraction spectra provided the best estimates for the Atterberg limits while a combination of spectra collected from fine and coarse (>2 mm diameter) fractions was effective in estimating other granulometric fractions except for sand, which was best estimated using the coarse fraction spectra. With the DSM approach allowing effective mapping of these parameters, a spatially-continuous framework to quantify soil-associated OVM risks was developed for Sikkim for the first time.

Spatial mapping of dengue fever prevalence and its association with geo-climatic factors in Lahore, Pakistan.

A vector-borne disease of concern for global public health, dengue fever has been spreading its endemicity and several cases in recent years, particularly in Lahore Pakistan. Dengue transmission is influenced by geo-climatic conditions. This study aimed to map the spatial prevalence of dengue fever in Lahore and its association with geo-climatic factors during the epidemic of the year 2021. In this study, geo-climatic factors that could potentially encourage the growth of the virus are chosen for this study, and their temporal and spatial changeability relate to dengue cases. The objective of this study is to use meteorological, satellite data and Geographic Information System (GIS) techniques to map dengue outbreaks and identify the risk-prone areas by relating geo-climatic factors with dengue outbreaks. The dengue patients and their locations data were collected from the Directorate General of Health Services (DGHS) Lahore. This study uses Google Earth and Landsat-8 OLI/TIRs images to extract geo-climatic and land use parameters. The dot density maps technique was used to represent the spatiotemporal distribution of dengue cases. The hotspot analysis was applied to show the hotspots of dengue cases in district Lahore at the Union Council (UC) level. The Normalised Difference Vegetation Index (NDVI), Normalised Difference Water Index (NDWI), built-up area, population density, precipitation, and Land Surface Temperature (LST) are the factors employed. In this study, correlation was performed to test the significance between precipitation and the prevalence of dengue fever in Lahore. The results show that the incidence and prevalence of dengue fever month-wise at the UC level in Lahore. The distribution pattern of dengue outbreaks in the Lahore area and its demographic factors were found to be associated. It concludes that the increase in the spread of dengue fever is associated with the monsoon rains. The prevalence of dengue is associated with water bodies and high land surface temperature, but it does not represent any significant relation with vegetation cover and land use in Lahore during the year 2021. The study pinpointed the locations that are most susceptible and require care to prevent such outbreaks in the future.

How far the types and wetland hydrological conditions influence its provisioning services in the Indian mature Ganges delta.

Present work intended to explore how far the Provisioning Service Value (PSV) of the mature Ganges deltaic wetlands is determined by its typology and a few physical attributes like hydrology and aquatic vegetations. Firstly, a field investigation was carried out in the representative sample sites, and field-measured PSV was calibrated with wetland types, hydrological security, and aquatic plant biomass to perform spatial estimation and mapping of PSV. The estimation yielded average annual PSV of entire wetlands as 146.5 × 105 Indian Rupee (INR)/km2/year, with the highest over bheries (embankments for fish and shrimp aquaculture) 176 × 105 INR/km2/year and lowest over marshy wetlands 107 × 105 INR/km2/year. Sensitivity analysis of this estimation showed in cases of 55% field visited sites, the field-measured PSV was outside the range of low standard regression residuals (-0.5 to 0.5). While searching for the reason behind such error in the estimation, the variability of the field-measured PSV was measured. Various inequality measures showed high inequality in inter and intra-hydrological conditions of the wetland. Analysis of variance (ANOVA) proved statistical significance of within-class variability. To explain the variability of PSV, Kernel Density Estimation (KDE) plotting was performed, incorporating a few other regional conditioning factors like wetland size, fish and shrimp aquaculture, perenniality, expenditure, and external feeding from the experience of the field. From this excesize, external feeding and expenditure were essential factors that should be incorporated along with the wetland characteristics and physical attributes for accurate estimation. Since producing spatial data layers of these factors with a finer resolution is difficult, the study suggests case-specific estimation of PSV instead of general spatial mapping.

Heterogeneity in biological assemblages and exposure in chemical risk assessment: Exploring capabilities and challenges in methodology with two landscape-scale case studies.

Chemical exposure concentrations and the composition of ecological receptors (e.g., species) vary in space and time, resulting in landscape-scale (e.g. catchment) heterogeneity. Current regulatory, prospective chemical risk assessment frameworks do not directly address this heterogeneity because they assume that reasonably worst-case chemical exposure concentrations co-occur (spatially and temporally) with biological species that are the most sensitive to the chemical's toxicity. Whilst current approaches may parameterise fate models with site-specific data and aim to be protective, a more precise understanding of when and where chemical exposure and species sensitivity co-occur enables risk assessments to be better tailored and applied mitigation more efficient. We use two aquatic case studies covering different spatial and temporal resolution to explore how geo-referenced data and spatial tools might be used to account for landscape heterogeneity of chemical exposure and ecological assemblages in prospective risk assessment. Each case study followed a stepwise approach: i) estimate and establish spatial chemical exposure distributions using local environmental information and environmental fate models; ii) derive toxicity thresholds for different taxonomic groups and determine geo-referenced distributions of exposure-toxicity ratios (i.e., potential risk); iii) overlay risk data with the ecological status of biomonitoring sites to determine if relationships exist. We focus on demonstrating whether the integration of relevant data and potential approaches is feasible rather than making comprehensive and refined risk assessments of specific chemicals. The case studies indicate that geo-referenced predicted environmental concentration estimations can be achieved with available data, models and tools but establishing the distribution of species assemblages is reliant on the availability of a few sources of biomonitoring data and tools. Linking large sets of geo-referenced exposure and biomonitoring data is feasible but assessment of risk will often be limited by the availability of ecotoxicity data. The studies highlight the important influence that choices for aggregating data and for the selection of statistical metrics have on assessing and interpreting risk at different spatial scales and patterns of distribution within the landscape. Finally, we discuss approaches and development needs that could help to address environmental heterogeneity in chemical risk assessment.

Canvas Painting Analysis Using Spectroscopic Analysis and Microcharacterisation Techniques.

Raman spectroscopy is a well-recognised tool for the analysis of materials in canvas paintings. However, it can be difficult to interpret the peaks of the spectra without the additional context of the artwork such as the age, provenance, or colour. Reflectance spectrophotometry can be used to capture the colour of pigments, dyes, and lacquers, but is seldom used to complement Raman data. Additionally, reflectance spectrophotometry results can be influenced by the surface profile of the painting. To overcome these limitations, this work brings together three different analysis modalities to provide a singular, analytical map of the artwork. Raman spectroscopy was used to conduct the chemical identification of pigments, binding media, and varnish present in a synthetic painting sample. Reflectance spectrophotometry was applied to obtain colour information of the surface paint of the sample. Three-dimensional optical profilometry data was used to characterise the micro topology of the paint surface. These three data sets were spatially matched allowing the recorded spectroscopic data to be displayed with the corresponding colour and surface topography across the paint surface.

Operando Direct Observation of Filament Formation in Resistive Switching Devices Enabled by a Topological Transformation Molecule.

Conductive filaments (CFs) play a critical role in the mechanism of resistive random-access memory (ReRAM) devices. However, in situ detection and visualization of the precise location of CFs are still key challenges. We demonstrate for the first time the use of a π-conjugated molecule which can transform between its twisted and planar states upon localized Joule heating generated within filament regions, thus reflecting the locations of the underlying CFs. Customized patterns of CFs were induced and observed by the π-conjugated molecule layer, which confirmed the hypothesis. Additionally, statistical studies on filaments distribution were conducted to study the effect of device sizes and bottom electrode heights, which serves to enhance the understanding of switching behavior and their variability at device level. Therefore, this approach has great potential in aiding the development of ReRAM technology.

High Accuracy Ultrafast Spatiotemporal Pump-Probe Measurement of Electrical Thermal Transport in Thin Film Gold.

A high resolution spatiotemporal ultrafast pump-probe system is developed to examine the interactions and transport phenomena between the electrical and the lattice thermal subsystems during ultrafast laser-matter interactions. This system incorporates an ultrafast pump-probe scheme with a stationary probe beam that interrogates the response to a spatial scanning pump beam, providing a full spatiotemporal mapping of a material's response due to an ultrafast pump excitation. The material's response, which is highly sensitive to its transport properties, is measured with a high spatial accuracy of up to ±10 nm and subpicosecond time resolution. Details of achieving this high spatial accuracy are described, and a study of the ultrafast transport processes in thin film gold is demonstrated. With the aid of transport and optical response models, the electrical thermal transport properties of gold and the electron-lattice coupling constant are simultaneously determined.

Advancing Sustainable Development Goals with localised nature-based solutions: Opportunity spaces in the Lahn river landscape, Germany.

Nature-based solutions (NBS) are recognized as promising actions to alleviate societal challenges and achieve the United Nation's Sustainable Development Goals (SDGs). One scientific challenge to implement NBS in practice is to locate areas suitable for an effective implementation of NBS (opportunity spaces). Opportunity spaces either already host NBS that need to be safeguarded or restored, or provide the socio-ecological conditions for establishing new NBS. Complex methods have been proposed to model potential locations of selected NBS, but they are often too data and resource intensive to be applied in practice for landscape planning. The aim of this article is to put forward a pragmatic method for identifying NBS opportunity spaces that contribute to advance multiple SDGs, and to test its application in a participatory, extended peer-review process in the Lahn river landscape, Germany. Our method includes: (i) synthesizing a generic catalogue of NBS in river landscapes, (ii) estimating the potential of NBS to achieve simultaneously Lahn development goals (LDGs) and SDGs, and (iii) applying key spatial indicators and best available data to explore opportunity spaces for selected NBS. The generic catalogue provides a systematic overview of 650 individual NBS for river landscapes and their respective potentials for addressing LDGs and SDGs. The NBS Renaturalising floodplains through land use changes, Revitalising historic floodplains, and Creating buffer strips are those actions contributing to the greatest number of local SDGs (locally adapted SDGs that include LDGs). Results of the spatial analysis in the Lahn river landscape showed about 4739 ha of areas where NBS were already in place and need to be safeguarded and additional 1323 ha with opportunities for further NBS creation. The proposed method presents a robust and transferable approach that facilitates spatial mapping of NBS to local SDGs for planning practitioners facing time and resource constraints.

Investigating the prescribing trajectory and geographical drug utilisation patterns of gabapentinoids in primary care in England: An ecological study.

AIMS: This study aimed to investigate the prescribing trajectory, geographical variation and population factors, including socioeconomic status (SES), related to prescribing gabapentinoids in primary care in England. METHODS: This ecological study applied practice-level dispensing data and statistics from the UK National Health Service Digital and Office for National Statistics from 2013 to 2019. The prescribing of gabapentinoids (in defined daily doses [DDDs]/1000 people) was measured annually and quarterly. General practices were categorised according to the quarterly prescribing in a group-based trajectory model. The one-year prescribing in 2018/19 was associated with practice-level covariates in a mixed-effects multilevel regression, adjusted for the cluster-effects of Clinical Commissioning Groups (CCGs) and mapped geographically. RESULTS: The annual national prescription rate increased by 70% from 2800 to 4773 DDDs/1000 people in the time period 2013/14 to 2018/19. General practices were stratified into six trajectory groups. Practices with the highest level and the greatest increase in prescribing (n = 789; 9.8%) are mainly located in the north of England and along the east and south coastline. Socioeconomic status, demographic characteristics and relevant disease conditions were significantly associated with the prescribing. For every decrease in the Index of Multiple Deprivation decile (becoming less affluent), prescribing of gabapentinoids increased significantly by 203 (95% CI: 183-222) DDDs/1000 registrants. CONCLUSIONS: Gabapentinoid prescribing trajectories varied across geographical regions and are associated with socioeconomic status, CCG locality (geography) and other population characteristics. These factors should be considered in future studies investigating the determinants of gabapentinoid prescribing and the risk of harms associated with gabapentinoids.

Neuronal Correlates of Many-To-One Sensorimotor Mapping in Lateral Intraparietal Cortex.

Efficiently mapping sensory stimuli onto motor programs is crucial for rapidly choosing appropriate behavioral responses. While neuronal mechanisms underlying simple, one-to-one sensorimotor mapping have been extensively studied, how the brain achieves complex, many-to-one sensorimotor mapping remains unclear. Here, we recorded single neuron activity from the lateral intraparietal (LIP) cortex of monkeys trained to map multiple spatial positions of visual cue onto two opposite saccades. We found that LIP neurons' activity was consistent with directly mapping multiple cue positions to the associated saccadic direction (SDir) regardless of whether the visual cue appeared in or outside neurons' receptive fields. Unlike the explicit encoding of the visual categories, such cue-target mapping (CTM)-related activity covaried with the associated SDirs. Furthermore, the CTM was preferentially mediated by visual neurons identified by memory-guided saccade. These results indicate that LIP plays a crucial role in the early stage of many-to-one sensorimotor transformation.

In Situ Wireless Channel Visualization Using Augmented Reality and Ray Tracing.

This article presents a novel methodology for predicting wireless signal propagation using ray-tracing algorithms, and visualizing signal variations in situ by leveraging Augmented Reality (AR) tools. The proposed system performs a special type of spatial mapping, capable of converting a scanned indoor environment to a vector facet model. A ray-tracing algorithm uses the facet model for wireless signal predictions. Finally, an AR application overlays the signal strength predictions on the physical space in the form of holograms. Although some indoor reconstruction models have already been developed, this paper proposes an image to a facet algorithm for indoor reconstruction and compares its performance with existing AR algorithms, such as spatial understanding that are modified to create the required facet models. In addition, the paper orchestrates AR and ray-tracing techniques to provide an in situ network visualization interface. It is shown that the accuracy of the derived facet models is acceptable, and the overall signal predictions are not significantly affected by any potential inaccuracies of the indoor reconstruction. With the expected increase of densely deployed indoor 5G networks, it is believed that these types of AR applications for network visualization will play a key role in the successful planning of 5G networks.

Geospatial variation in co-occurrence networks of nitrifying microbial guilds.

Microbial communities transform nitrogen (N) compounds, thereby regulating the availability of N in soil. The N cycle is defined by interacting microbial functional groups, as inorganic N-products formed in one process are the substrate in one or several other processes. The nitrification pathway is often a two-step process in which bacterial or archaeal communities oxidize ammonia to nitrite, and bacterial communities further oxidize nitrite to nitrate. Little is known about the significance of interactions between ammonia-oxidizing bacteria (AOB) and archaea (AOA) and nitrite-oxidizing bacterial communities (NOB) in determining the spatial variation of overall nitrifier community structure. We hypothesize that nonrandom associations exist between different AO and NOB lineages that, along with edaphic factors, shape field-scale spatial patterns of nitrifying communities. To address this, we sequenced and quantified the abundance of AOA, AOB, and Nitrospira and Nitrobacter NOB communities across a 44-hectare site with agricultural fields. The abundance of Nitrobacter communities was significantly associated only with AOB abundance, while that of Nitrospira was correlated to AOA. Network analysis and geostatistical modelling revealed distinct modules of co-occurring AO and NOB groups occupying disparate areas, with each module dominated by different lineages and associated with different edaphic factors. Local communities were characterized by a high proportion of module-connecting versus module-hub nodes, indicating that nitrifier assemblages in these soils are shaped by fluctuating conditions. Overall, our results demonstrate the utility of network analysis in accounting for potential biotic interactions that define the niche space of nitrifying communities at scales compatible to soil management.

Probing Adsorption Configurations of Small Molecules on Surfaces by Single-Molecule Tip-Enhanced Raman Spectroscopy.

Determining the adsorption configurations of organic molecules on surfaces, especially for relatively small molecules, is a key issue for understanding the microscopic physical and chemical processes in surface science. In this work, we have applied low-temperature ultrahigh-vacuum tip-enhanced Raman scattering (TERS) technique to distinguish the configurations of small 4,4'-bipyridine (44BPY) molecules adsorbed on the Ag(111) surface. The observed Raman spectra exhibit notable differences in the spectral features which can be assigned to three different molecular orientations, each featuring a specific fingerprint pattern based on the TERS selection rule that determines the distribution of the relative intensities of different vibrational peaks. Furthermore, such a small molecule can in turn act as a local probe to provide information on the local electric field distribution at the tip apex. Our work showcases the capability of TERS technique for obtaining information on adsorption configurations of small molecules on surfaces down to the single-molecule level, which is of fundamental importance for many applications in the fields of molecular science and surface chemistry.

Assessing spatial variability of extreme hot weather conditions in Hong Kong: A land use regression approach.

The number of extreme hot weather events have considerably increased in Hong Kong in the recent decades. The complex urban context of Hong Kong leads to a significant intra-urban spatial variability in climate. Under such circumstance, a spatial understanding of extreme hot weather condition is urgently needed for heat risk prevention and public health actions. In this study, the extreme hot weather events of Hong Kong were quantified and measured using two indicators - very hot day hours (VHDHs) and hot night hours (HNHs) which were counted based on the summertime hourly-resolved air temperature data from a total of 40 weather stations (WSs) from 2011 to 2015. Using the VHDHs and HNHs at the locations of the 40 WSs as the outcome variables, land use regression (LUR) models are developed to achieve a spatial understanding of the extreme hot weather conditions in Hong Kong. Land surface morphology was quantified as the predictor variables in LUR modelling. A total of 167 predictor variables were considered in the model development process based on a stepwise multiple linear regression (MLR). The performance of resultant LUR models was evaluated via cross validation. VHDHs and HNHs were mapped at the community level for Hong Kong. The mapping results illustrate a significant spatial variation in the extreme hot weather conditions of Hong Kong in both the daytime and nighttime, which indicates that the spatial variation of land use configurations must be considered in the risk assessment and corresponding public health management associated with the extreme hot weather.

Spatial order relates to the exact numerical magnitude of digits in young children.

Spatial representation of numbers has been repeatedly associated with the development of numerical and mathematical skills. However, few studies have explored the contribution of spatial mapping to exact number representation in young children. Here we designed a novel task that allows a detailed analysis of direction, ordinality, and accuracy of spatial mapping. Preschool children, who were classified as competent counters (cardinal principle knowers), placed triplets of sequentially presented digits on the visual line. The ability to correctly order triplets tended to decrease with the larger digits. When triplets were correctly ordered, the direction of spatial mapping was predominantly oriented from left to right and the positioning of the target digits was characterized by a pattern of underestimation with no evidence of logarithmic compression. Crucially, only ordinality was associated with performance in a digit comparison task. Our results suggest that the spatial (ordinal) arrangement of digits is a powerful source of information that young children can use to construct the representation of exact numbers. Therefore, digits may acquire numerical meaning based on their spatial order on the number line.