High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue.

We present deterministic barcoding in tissue for spatial omics sequencing (DBiT-seq) for co-mapping of mRNAs and proteins in a formaldehyde-fixed tissue slide via next-generation sequencing (NGS). Parallel microfluidic channels were used to deliver DNA barcodes to the surface of a tissue slide, and crossflow of two sets of barcodes, A1-50 and B1-50, followed by ligation in situ, yielded a 2D mosaic of tissue pixels, each containing a unique full barcode AB. Application to mouse embryos revealed major tissue types in early organogenesis as well as fine features like microvasculature in a brain and pigmented epithelium in an eye field. Gene expression profiles in 10-µm pixels conformed into the clusters of single-cell transcriptomes, allowing for rapid identification of cell types and spatial distributions. DBiT-seq can be adopted by researchers with no experience in microfluidics and may find applications in a range of fields including developmental biology, cancer biology, neuroscience, and clinical pathology.

Advances in mass spectrometry imaging for plant metabolomics-Expanding the analytical toolbox.

Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi-omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years.

Spatial Proteomic Profiling of Colorectal Cancer Revealed Its Tumor Microenvironment Heterogeneity.

Colorectal cancer is a predominant malignancy with a second mortality worldwide. Despite its prevalence, therapeutic options remain constrained and surgical operation is still the most useful therapy. In this regard, a comprehensive spatially resolved quantitative proteome atlas was constructed to explore the functional proteomic landscape of colorectal cancer. This strategy integrates histopathological analysis, laser capture microdissection, and proteomics. Spatial proteome profiling of 200 tissue section samples facilitated by the fully integrated sample preparation technology SISPROT enabled the identification of more than 4000 proteins on the Orbitrap Exploris 240 from 2 mm2 × 10 µm tissue sections. Compared with normal adjacent tissues, we identified a spectrum of cancer-associated proteins and dysregulated pathways across various regions of colorectal cancer including ascending colon, transverse colon, descending colon, sigmoid colon, and rectum. Additionally, we conducted proteomic analysis on tumoral epithelial cells and paracancerous epithelium from early to advanced stages in hallmark rectum cancer and sigmoid colon cancer. Bioinformatics analysis revealed functional proteins and cell-type signatures associated with different regions of colorectal tumors, suggesting potential clinical implications. Overall, this study provides a comprehensive spatially resolved functional proteome landscape of colorectal cancer, serving as a valuable resource for exploring potential biomarkers and therapeutic targets.

MALDI MSI Protocol for Spatial Bottom-Up Proteomics at Single-Cell Resolution.

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) started with spatial mapping of peptides and proteins. Since then, numerous bottom-up protocols have been developed. However, achievable spatial resolution and sample preparation with many wet steps hindered the development of single cell-level workflows for bottom-up spatial proteomics. This study presents a protocol optimized for MALDI-MSI measurements of single cells within the context of their 2D culture. Sublimation of CHCA, followed by a dip in ice-cold ammonium phosphate monobasic (AmP), produced peptide-rich mass spectra while maintaining matrix crystal sizes around 400 nm. This enables MALDI-MSI imaging of proteins in single cells grown on an ITO slide with a throughput of approximately 7800 cells per day. 89 peptide-like features corresponding to a single MDA-MB-231 breast cancer cell were detected. Furthermore, by combining the MALDI-MSI data with LC-MS/MS data obtained on cell pellets, we have successfully identified 24 peptides corresponding to 17 proteins, including actin, vimentin, and transgelin-2.

Signal-to-noise and spatial resolution in in-line imaging. 1. Basic theory, numerical simulations and planar experimental images.

Signal-to-noise ratio and spatial resolution are quantitatively analysed in the context of in-line (propagation based) X-ray phase-contrast imaging. It is known that free-space propagation of a coherent X-ray beam from the imaged object to the detector plane, followed by phase retrieval in accordance with Paganin's method, can increase the signal-to-noise in the resultant images without deteriorating the spatial resolution. This results in violation of the noise-resolution uncertainty principle and demonstrates `unreasonable' effectiveness of the method. On the other hand, when the process of free-space propagation is performed in software, using the detected intensity distribution in the object plane, it cannot reproduce the same effectiveness, due to the amplification of photon shot noise. Here, it is shown that the performance of Paganin's method is determined by just two dimensionless parameters: the Fresnel number and the ratio of the real decrement to the imaginary part of the refractive index of the imaged object. The relevant theoretical analysis is performed first, followed by computer simulations and then by a brief test using experimental images collected at a synchrotron beamline. More extensive experimental tests will be presented in the second part of this paper.

Reduced physiology-induced temporal instability achieved with variable-flip-angle fast low-angle excitation echo-planar technique with multishot echo planar time-resolved imaging.

PURPOSE: Echo planar time-resolved imaging (EPTI) is a new imaging approach that addresses the limitations of EPI by providing high-resolution, distortion- and T2/ T 2 * $$ {\mathrm{T}}_2^{\ast } $$  blurring-free imaging for functional MRI (fMRI). However, as in all multishot sequences, intershot phase variations induced by physiological processes can introduce temporal instabilities to the reconstructed time-series data. This study aims to reduce these instabilities in multishot EPTI. THEORY AND METHODS: In conventional multishot EPTI, the time intervals between the shots comprising each slice can introduce intershot phase variations. Here, the fast low-angle excitation echo-planar technique (FLEET), in which all shots of each slice are acquired consecutively with minimal time delays, was combined with a variable flip angle (VFA) technique to improve intershot consistency and maximize signal. A recursive Shinnar-Le Roux RF pulse design algorithm was used to generate pulses for different shots to produce consistent slice profiles and signal intensities across shots. Blipped controlled aliasing in parallel imaging simultaneous multislice was also combined with the proposed VFA-FLEET EPTI to improve temporal resolution and increase spatial coverage. RESULTS: The temporal stability of VFA-FLEET EPTI was compared with conventional EPTI at 7 T. The results demonstrated that VFA-FLEET can provide spatial-specific increase of temporal stability. We performed high-resolution task-fMRI experiments at 7 T using VFA-FLEET EPTI, and reliable BOLD responses to a visual stimulus were detected. CONCLUSION: The intershot phase variations induced by physiological processes in multishot EPTI can manifest as specific spatial patterns of physiological noise enhancement and lead to reduced temporal stability. The VFA-FLEET technique can substantially reduce these physiology-induced instabilities in multishot EPTI acquisitions. The proposed method provides sufficient stability and sensitivity for high-resolution fMRI studies.

Comprehensive assessment of nonuniform image quality: Application to imaging near metal.

PURPOSE: Comprehensive assessment of image quality requires accounting for spatial variations in (i) intensity artifact, (ii) geometric distortion, (iii) signal-to-noise ratio (SNR), and (iv) spatial resolution, among other factors. This work presents an ensemble of methods to meet this need, from phantom design to image analysis, and applies it to the scenario of imaging near metal. METHODS: A modular phantom design employing a gyroid lattice is developed to enable the co-registered volumetric quantitation of image quality near a metallic hip implant. A method for measuring spatial resolution by means of local point spread function (PSF) estimation is presented and the relative fitness of gyroid and cubic lattices is examined. Intensity artifact, geometric distortion, and SNR maps are also computed. Results are demonstrated with 2D-FSE and MAVRIC-SL scan protocols on a 3T MRI scanner. RESULTS: The spatial resolution method demonstrates a worst-case error of 0.17 pixels for measuring in-plane blurring up to 3 pixels (full width at half maximum). The gyroid outperforms a cubic lattice design for the local PSF estimation task. The phantom supports four configurations toggling the presence/absence of both metal and structure with good spatial correspondence for co-registered analysis of the four quality factors. The marginal scan time to evaluate one scan protocol amounts to five repetitions. The phantom design can be fabricated in 2 days at negligible material cost. CONCLUSION: The phantom and associated analysis methods can elucidate complex image quality trade-offs involving intensity artifact, geometric distortion, SNR, and spatial resolution. The ensemble of methods is suitable for benchmarking imaging performance near metal.

Phantom evaluation of electrical conductivity mapping by MRI: Comparison to vector network analyzer measurements and spatial resolution assessment.

PURPOSE: To evaluate the performance of various MR electrical properties tomography (MR-EPT) methods at 3 T in terms of absolute quantification and spatial resolution limit for electrical conductivity. METHODS: Absolute quantification as well as spatial resolution performance were evaluated on homogeneous phantoms and a phantom with holes of different sizes, respectively. Ground-truth conductivities were measured with an open-ended coaxial probe connected to a vector network analyzer (VNA). Four widely used MR-EPT reconstruction methods were investigated: phase-based Helmholtz (PB), phase-based convection-reaction (PB-cr), image-based (IB), and generalized-image-based (GIB). These methods were compared using the same complex images from a 1 mm-isotropic UTE sequence. Alternative transceive phase acquisition sequences were also compared in PB and PB-cr. RESULTS: In large homogeneous phantoms, all methods showed a strong correlation with ground truth conductivities (r > 0.99); however, GIB was the best in terms of accuracy, spatial uniformity, and robustness to boundary artifacts. In the resolution phantom, the normalized root-mean-squared error of all methods grew rapidly (>0.40) when the hole size was below 10 mm, with simplified methods (PB and IB), or below 5 mm, with generalized methods (PB-cr and GIB). CONCLUSION: VNA measurements are essential to assess the accuracy of MR-EPT. In this study, all tested MR-EPT methods correlated strongly with the VNA measurements. The UTE sequence is recommended for MR-EPT, with the GIB method providing good accuracy for structures down to 5 mm. Structures below 5 mm may still be detected in the conductivity maps, but with significantly lower accuracy.

A tutorial: Laserspray ionization and related laser-based ionization methods for use in mass spectrometry.

This Tutorial is to provide a summary of parameters useful for successful outcomes of laserspray ionization (LSI) and related methods that employ a laser to ablate a matrix:analyte sample to produce highly charged ions. In these methods the purpose of the laser is to transfer matrix-analyte clusters into the gas phase. Ions are hypothesized to be produced by a thermal process where emitted matrix:analyte gas-phase particles/clusters are charged and loss of matrix from the charged particles leads to release of the analyte ions into the gas phase. The thermal energy responsible for the charge-separation process is relatively low and not necessarily supplied by the laser; a heated inlet tube linking atmospheric pressure with the first vacuum stage of a mass spectrometer is sufficient. The inlet becomes the "ion source", and inter alia, pressure, temperature, and the matrix, which can be a solid, liquid, or combinations, become critical parameters. Injecting matrix:analyte into a heated inlet tube using laser ablation, a shockwave, or simply tapping, all produce the similar mass spectra. Applications are provided that showcase new opportunities in the field of mass spectrometry.

Diffusion and Exchange Kinetics of Microparticle Formulations by Spatial Fourier Transform Fluorescence Recovery after Photobleaching with Patterned Illumination.

The mechanism of active pharmaceutical ingredient (API) mobility during release in microparticle formulation was investigated using periodically structured illumination combined with spatial Fourier transform fluorescence recovery after photobleaching (FT-FRAP). FT-FRAP applies structured photobleaching across a given field of view, allowing for the monitoring of molecular mobility through the analysis of recovery patterns in the FT domain. Encoding molecular mobility in the FT domain offers several advantages, including improved signal-to-noise ratio, simplified mathematical calculations, reduced sampling requirements, compatibility with multiphoton microscopy for imaging API molecules within the formulations, and the ability to distinguish between exchange and diffusion processes. To prepare microparticles for FT-FRAP analysis, a homogeneous mixture of dipyridamole and pH-independent methyl methacrylate polymer (Eudragit RS and RL) was processed using laminar jet breakup induced by vibration in a frequency-driven encapsulator. The encapsulated microparticles were characterized based on particle size distribution, encapsulation efficiency, batch size, and morphology. Utilizing FT-FRAP, the internal diffusion and exchange molecular mobility within RL and RS microparticles were discriminated and quantified. Theoretical modeling of exchange- and diffusion-controlled release revealed that both RL and RS microparticles exhibited similar exchange decay rates, but RL displayed a significantly higher diffusion coefficient. This difference in diffusion within RL and RS microparticles was correlated with their macroscopic dissolution performance.

Ecological and morphological correlates of visual acuity in birds.

Birds use their visual systems for important tasks, such as foraging and predator detection, that require them to resolve an image. However, visual acuity (the ability to perceive spatial detail) varies by two orders of magnitude across birds. Prior studies indicate that eye size and aspects of a species' ecology may drive variation in acuity, but these studies have been restricted to small numbers of species. We used a literature review to gather data on acuity measured either behaviorally or anatomically for 94 species from 38 families. We then examined how acuity varies in relation to (1) eye size, (2) habitat spatial complexity, (3) habitat light level, (4) diet composition, (5) prey mobility and (6) foraging mode. A phylogenetically controlled model including all of the above factors as predictors indicated that eye size and foraging mode are significant predictors of acuity. Examining each ecological variable in turn revealed that acuity is higher in species whose diet comprises vertebrates or scavenged food and whose foraging modes require resolving prey from farther away. Additionally, species that live in spatially complex, vegetative habitats have lower acuity than expected for their eye sizes. Together, our results suggest that the need to detect important objects from far away - such as predators for species that live in open habitats, and food items for species that forage on vertebrate and scavenged prey - has likely been a key driver of higher acuity in some species, helping us to elucidate how visual capabilities may be adapted to an animal's visual needs.

Analyses of high spatial resolution datasets identify genes associated with multi-layered secondary cell wall thickening in Pinus bungeana.

BACKGROUND AND AIMS: Secondary cell wall (SCW) thickening is a major cellular developmental stage determining wood structure and properties. Although the molecular regulation of cell wall deposition during tracheary element differentiation has been well established in primary growth systems, less is known about the gene regulatory processes involved in the multi-layered SCW thickening of mature trees. METHODS: Using third-generation [long-read single-molecule real-time (SMRT)] and second-generation [short-read sequencing by synthesis (SBS)] sequencing methods, we established a Pinus bungeana transcriptome resource with comprehensive functional and structural annotation for the first time. Using these approaches, we generated high spatial resolution datasets for the vascular cambium, xylem expansion regions, early SCW thickening, late SCW thickening and mature xylem tissues of 71-year-old Pinus bungeana trees. KEY RESULTS: A total of 79 390 non-redundant transcripts, 31 808 long non-coding RNAs and 5147 transcription factors were annotated and quantified in different xylem tissues at all growth and differentiation stages. Furthermore, using this high spatial resolution dataset, we established a comprehensive transcriptomic profile and found that members of the NAC, WRKY, SUS, CESA and LAC gene families are major players in early SCW formation in tracheids, whereas members of the MYB and LBD transcription factor families are highly expressed during late SCW thickening. CONCLUSIONS: Our results provide new molecular insights into the regulation of multi-layered SCW thickening in conifers. The high spatial resolution datasets provided can serve as important gene resources for improving softwoods.

Spatiotemporal variability of the association between greenspace exposure and depression in older adults in South Korea.

BACKGROUND: A number of studies based on young to middle aged adult and child samples have found that exposure to greenspace and bluespace can have a positive impact on mental health and well-being. However, there is limited research among older adults and the extant studies have provided mixed results. The present study was designed to examine how the association between these forms of exposure and depressive symptoms among older adults varies as a function of different spatially and temporally resolved exposure metrics. METHODS: The sample consisted of 617 individuals (46.19% female) aged ≥ 60 years of age. Depressive symptoms were measured using the 10-item Center for Epidemiological Studies Depression Scale (CES-D). Individuals' greenspace exposure was quantified using spatially and temporally resolved metrics, including monthly and annual averaged satellite-derived normalized difference vegetation index (NDVI) across multiple buffer distances (250 m to 2,000 m) centered at participants' home address. We also quantified exposure to blue-greenspace from a highly detailed land use and land cover dataset. A multivariable logistic regression model assessed the association between greenspace and blue-greenspace exposure and depressive symptoms, adjusting for age, sex, income, education, marital status, current smoking, alcohol status, medical conditions, temperature, crime rate, population density, and per capita park area. RESULTS: We found a significant association between exposures to greenspace and blue-greenspace and depressive symptoms (CES-D cutoff ≥ 4) among older adults. After adjusting for confounding variables, the odds of depressive symptoms were significantly decreased by an IQR increment in residential exposure to greenspace [odds ratio (OR) = 0.67; 95% confidence interval (95% CI), 0.49 ~ 0.91] and blue-greenspace (OR = 0.59; 95% CI, 0.41 ~ 0.84) measured nearby their home address (i.e., as close as 250 m). When stratified by household income level, the association was only significant among low-income individuals. We also found temporal variation in the association between depressive symptoms and monthly NDVI-based greenspace exposure, in which the odds of depressive symptoms were the lowest for greenspace in cold months (i.e., January, February, and March). CONCLUSIONS: Our findings suggest that neighborhood greenspace may serve as a protective factor against depression among older adults, but the benefits may depend on the spatial and temporal context. More investigation is needed to replicate our findings on the spatial and temporal variations of greenspace exposure metrics and their effects on depressive symptoms.

Multiplanar reconstructions of the thoracic spine in a photon counting dual-source CT scanner: comparison to EID-CT.

BACKGROUND: Photon-counting detector computed tomography (PCD-CT) is a groundbreaking technology with promising results for visualization of small bone structures. PURPOSE: To analyze the delineation of the thoracic spine in multiplanar reconstructions (MPR) on PCD-CT compared to energy-integrating detector (EID)-CT. MATERIAL AND METHODS: Two euthanized mice were examined using different scanners: (i) 20-slice EID-CT and (ii) dual-source PCD-CT at various CTDIVol values. Readers evaluated the thoracic spine and selected series with best visualization among signal-to-noise ratio (SNR)-matched pairs. RESULTS: SNR was significantly higher in PCD-CT reconstructions (Br68) and lower in Hr98 reconstructions compared to EID-CT. Bone detail visualization was superior in PCD-CT (especially in Hr98 reconstructions) compared to EID-CT. CONCLUSION: MPR on a PCD-CT had a higher SNR and better bone detail visualization even at lower radiation doses compared to EID-CT. PCD-CT with bone reconstructions showed the best delineation of small bone structures and might be considered in clinical routine.

An image-computable model of how endogenous and exogenous attention differentially alter visual perception.

Attention alters perception across the visual field. Typically, endogenous (voluntary) and exogenous (involuntary) attention similarly improve performance in many visual tasks, but they have differential effects in some tasks. Extant models of visual attention assume that the effects of these two types of attention are identical and consequently do not explain differences between them. Here, we develop a model of spatial resolution and attention that distinguishes between endogenous and exogenous attention. We focus on texture-based segmentation as a model system because it has revealed a clear dissociation between both attention types. For a texture for which performance peaks at parafoveal locations, endogenous attention improves performance across eccentricity, whereas exogenous attention improves performance where the resolution is low (peripheral locations) but impairs it where the resolution is high (foveal locations) for the scale of the texture. Our model emulates sensory encoding to segment figures from their background and predict behavioral performance. To explain attentional effects, endogenous and exogenous attention require separate operating regimes across visual detail (spatial frequency). Our model reproduces behavioral performance across several experiments and simultaneously resolves three unexplained phenomena: 1) the parafoveal advantage in segmentation, 2) the uniform improvements across eccentricity by endogenous attention, and 3) the peripheral improvements and foveal impairments by exogenous attention. Overall, we unveil a computational dissociation between each attention type and provide a generalizable framework for predicting their effects on perception across the visual field.

Spatial Resolution Enhancement Framework Using Convolutional Attention-Based Token Mixer.

Spatial resolution enhancement in remote sensing data aims to augment the level of detail and accuracy in images captured by satellite sensors. We proposed a novel spatial resolution enhancement framework using the convolutional attention-based token mixer method. This approach leveraged spatial context and semantic information to improve the spatial resolution of images. This method used the multi-head convolutional attention block and sub-pixel convolution to extract spatial and spectral information and fused them using the same technique. The multi-head convolutional attention block can effectively utilize the local information of spatial and spectral dimensions. The method was tested on two kinds of data types, which were the visual-thermal dataset and the visual-hyperspectral dataset. Our method was also compared with the state-of-the-art methods, including traditional methods and deep learning methods. The experiment results showed that the method was effective and outperformed state-of-the-art methods in overall, spatial, and spectral accuracies.

Improved Small Object Detection Algorithm CRL-YOLOv5.

Detecting small objects in images poses significant challenges due to their limited pixel representation and the difficulty in extracting sufficient features, often leading to missed or false detections. To address these challenges and enhance detection accuracy, this paper presents an improved small object detection algorithm, CRL-YOLOv5. The proposed approach integrates the Convolutional Block Attention Module (CBAM) attention mechanism into the C3 module of the backbone network, which enhances the localization accuracy of small objects. Additionally, the Receptive Field Block (RFB) module is introduced to expand the model's receptive field, thereby fully leveraging contextual information. Furthermore, the network architecture is restructured to include an additional detection layer specifically for small objects, allowing for deeper feature extraction from shallow layers. When tested on the VisDrone2019 small object dataset, CRL-YOLOv5 achieved an mAP50 of 39.2%, representing a 5.4% improvement over the original YOLOv5, effectively boosting the detection precision for small objects in images.

Experimental Demonstration of a Tunable Energy-Selective Gamma-Ray Imaging System Based on Recoil Electrons.

The domain of gamma-ray imaging necessitates technological advancements to surmount the challenge of energy-selective imaging. Conventional systems are constrained in their dynamic focus on specific energy ranges, a capability imperative for differentiating gamma-ray emissions from diverse sources. This investigation introduces an innovative imaging system predicated on the detection of recoil electrons, addressing the demand for adjustable energy selectivity. Our methodology encompasses the design of a gamma-ray imaging system that leverages recoil electron detection to execute energy-selective imaging. The system's efficacy was investigated experimentally, with emphasis on the adaptability of the energy selection window. The experimental outcomes underscore the system's adeptness at modulating the energy selection window, adeptly discriminating gamma rays across a stipulated energy spectrum. The results corroborate the system's adaptability, with an adjustable energy resolution that coincides with theoretical projections and satisfies the established criteria. This study affirms the viability and merits of utilizing recoil electrons for tunable energy-selective gamma-ray imaging. The system's conceptualization and empirical validation represent a notable progress in gamma-ray imaging technology, with prospective applications extending from medical imaging to astrophysics. This research sets a solid foundation for subsequent inquiries and advancements in this domain.

A Miniaturized Ultrawideband V-Shaped Tip E-Probe for Near-Field Measurements.

A sensitive, miniaturized, ultrawideband probe is proposed for near-field measurements. The proposed probe is based on a new V-shaped tip design and a slope structure resulting in better field distribution and impedance matching with a span bandwidth from 10 kHz up to 52 GHz, which is compatible with ultrawideband applications. The proposed E-probe fabrication process utilizes a four-layer printed circuit board (PCB) using Rogers RO4003 (tm) and RO4450 high-performance dielectrics, with εr = 3.55 and 3.3, respectively. The probe length is 40 mm with a minimum width of 4 mm, which is suitable for narrow, complex, and integrated PCBs. The passive E-probe sensitivity is -106.29 dBm and -87.48 dBm at 2 GHz and 40 GHz, respectively. It has a very small spatial resolution of 0.5 mm at 20, 25, 30, and 35 GHz. The probe is small and cheap and can diagnose electromagnetic interference (EMI) in electronic systems such as telemetry, UAVs, and avionics.

Impacts of Spatial Resolution and XCO2 Precision on Satellite Capability for CO2 Plumes Detection.

Greenhouse gas satellites can provide consistently global CO2 data which are important inputs for the top-down inverse estimation of CO2 emissions and their dynamic changes. By tracking greenhouse gas emissions, policymakers and businesses can identify areas where reductions are needed most and implement effective strategies to reduce their impact on the environment. Monitoring greenhouse gases provides valuable data for scientists studying climate change. The requirements for CO2 emissions monitoring and verification support capacity drive the payload design of future CO2 satellites. In this study, we quantitatively evaluate the performance of satellite in detecting CO2 plumes from power plants based on an improved Gaussian plume model, with focus on impacts of the satellite spatial resolution and the satellite-derived XCO2 precision under different meteorological conditions. The simulations of CO2 plumes indicate that the enhanced spatial resolution and XCO2 precision can significantly improve the detection capability of satellite, especially for small-sized power plants with emissions below 6 Mt CO2/yr. The satellite-detected maximum of XCO2 enhancement strongly varies with the wind condition. For a satellite with a XCO2 precision of 0.7 ppm and a spatial resolution of 2 km, it can recognize a power plant with emissions of 2.69 Mt CO2/yr at a wind speed of 2 m/s, while its emission needs be larger than 5.1 Mt CO2/yr if the power plant is expected to be detected at a wind speed of 4 m/s. Considering the uncertainties in the simulated wind field, the satellite-derived XCO2 measurements and the hypothesized CO2 emissions, their cumulative contribution to the overall accuracy of the satellite's ability to identify realistic enhancement in XCO2 are investigated in the future. The uncertainties of ΔXCO2 caused by the uncertainty in wind speed is more significant than those introduced from the uncertainty in wind direction. In the case of a power plant emitting 5.1 Mt CO2/yr, with the wind speed increasing from 0.5 m/s to 4 m/s, the simulated ΔXCO2 uncertainty associated with the wind field ranges from 3.75 ± 2.01 ppm to 0.46 ± 0.24 ppm and from 1.82 ± 0.95 ppm to 0.22 ± 0.11 ppm for 1 × 1 km2 and 2 × 2 km2 pixel size, respectively. Generally, even for a wind direction with a higher overall uncertainty, satellite still has a more effective capability for detecting CO2 emission on this wind direction, because there is more rapid growth for simulated maximal XCO2 enhancements than that for overall uncertainties. A designed spatial resolution of satellite better than 1 km and a XCO2 precision higher than 0.7 ppm are suggested, because the CO2 emission from small-sized power plants is much more likely be detected when the wind speed is below 3 m/s. Although spatial resolution and observed precision parameters are not sufficient to support the full design of future CO2 satellites, this study still can provide valuable insights for enhancing satellite monitoring of anthropogenic CO2 emissions.