High Spatiotemporal Resolution Research Articles

Live Single-Cell Transcriptional Dynamics in Plant Cells.

Transcriptional reprogramming plays a key role in a variety of biological processes. Recent advances in RNA imaging techniques have allowed to visualize, in vivo, transcription-related mechanisms in different organisms. The MS2 system constitutes a robust method that has been used for over two decades to image multiple steps of a transcript's life cycle from "birth to death" with high spatiotemporal resolution in the animal field. It is based on the high affinity binding of the MS2 bacteriophage coat protein to its RNA hairpin ligands. Despite its broad applicability, a limited number of studies have implemented the system in plants, but without exploiting its full potential. Here, we describe the transposition of the MS2 technique to Arabidopsis. Combined with microfluidics, it allows to visualize the transcriptional repression of a phosphate starvation induced gene (SPX1) upon phosphate refeeding in vivo. The system provided access to the transcriptional response kinetics of individual cells, gene expression heterogeneity, and revealed bursting phenomena in plantae. The described methods provide new insights for multiple applications.

Simultaneous detection of membrane contact dynamics and associated Ca2+ signals by reversible chemogenetic reporters.

Membrane contact sites (MCSs) are hubs allowing various cell organelles to coordinate their activities. The dynamic nature of these sites and their small size hinder analysis by current imaging techniques. To overcome these limitations, we here design a series of reversible chemogenetic reporters incorporating improved, low-affinity variants of splitFAST, and study the dynamics of different MCSs at high spatiotemporal resolution, both in vitro and in vivo. We demonstrate that these versatile reporters suit different experimental setups well, allowing one to address challenging biological questions. Using these probes, we identify a pathway in which calcium (Ca2+) signalling dynamically regulates endoplasmic reticulum-mitochondria juxtaposition, characterizing the underlying mechanism. Finally, by integrating Ca2+-sensing capabilities into the splitFAST technology, we introduce PRINCESS (PRobe for INterorganelle Ca2+-Exchange Sites based on SplitFAST), a class of reporters to simultaneously detect MCSs and measure the associated Ca2+ dynamics using a single biosensor.

Photoresponsive Adenosine Derivatives for the Optical Control of Adenosine A2A Receptors in Living Cells.

The use of photoresponsive ligands to optically control proteins of interest, known as photopharmacology, is a powerful technique for elucidating cellular function in living cells and animals with a high spatiotemporal resolution. The adenosine A2A receptor (A2AR) is a G protein-coupled receptor that is expressed in various tissues; its dysregulation is implicated in severe diseases such as insomnia and Parkinson's disease. A detailed elucidation of the physiological function of A2AR is, therefore, highly desirable. In the present study, we developed two photoswitchable ligands, photoAd(blue) and photoAd(vio), that target A2AR. Using photoAd(vio), we successfully demonstrated the selective activation of A2AR in living cells by violet-light irradiation with high spatiotemporal resolution.

Electric-Field-Driven Redistribution of Carriers on Catalyst Particles to Improve Photocatalytic Performance.

The photocatalytic performance is primarily determined by carrier separation efficiency. Applying electric fields to enhance carrier separation efficiency and thereby boost catalytic performance has emerged as a promising approach. However, the carrier behavior on catalyst particles under electric fields was still hardly acknowledged. Herein, using single-molecule fluorescence microscopy with high spatiotemporal resolution, the redistribution behavior of carriers on catalyst particles under an electric field was visualized for the first time, which was closely related to the direction and intensity of the electric field. Single-molecule kinetics of the photocatalytic redox reactions induced by carriers have been further obtained, and the results showed that the external electric field had an obvious regulating role in the conversion process and desorption process in this work, which was attributed to the dynamic redistribution of carriers. The improvement of photocatalytic hydrogen evolution reaction (HER) activity further supports the impact of the external electric field on photocatalysis. This work offers new insight into the microscopic regulation mechanism of photocatalytic activity by electric fields and provides new methods for studying the structure-activity relationship in photocatalytic processes.

Daily PM2.5 and Seasonal-Trend Decomposition to Identify Extreme Air Pollution Events from 2001 to 2020 for Continental Australia Using a Random Forest Model

Robust high spatiotemporal resolution daily PM2.5 exposure estimates are limited in Australia. Estimates of daily PM2.5 and the PM2.5 component from extreme pollution events (e.g., bushfires and dust storms) are needed for epidemiological studies and health burden assessments attributable to these events. We sought to: (1) estimate daily PM2.5 at a 5 km × 5 km spatial resolution across the Australian continent between 1 January 2001 and 30 June 2020 using a Random Forest (RF) algorithm, and (2) implement a seasonal-trend decomposition using loess (STL) methodology combined with selected statistical flags to identify extreme events and estimate the extreme pollution PM2.5 component. We developed an RF model that achieved an out-of-bag R-squared of 71.5% and a root-mean-square error (RMSE) of 4.5 µg/m3. We predicted daily PM2.5 across Australia, adequately capturing spatial and temporal variations. We showed how the STL method in combination with statistical flags can identify and quantify PM2.5 attributable to extreme pollution events in different locations across the country.

A broadband hyperspectral image sensor with high spatio-temporal resolution

Hyperspectral imaging provides high-dimensional spatial–temporal–spectral information showing intrinsic matter characteristics1–5. Here we report an on-chip computational hyperspectral imaging framework with high spatial and temporal resolution. By integrating different broadband modulation materials on the image sensor chip, the target spectral information is non-uniformly and intrinsically coupled to each pixel with high light throughput. Using intelligent reconstruction algorithms, multi-channel images can be recovered from each frame, realizing real-time hyperspectral imaging. Following this framework, we fabricated a broadband visible–near-infrared (400–1,700 nm) hyperspectral image sensor using photolithography, with an average light throughput of 74.8% and 96 wavelength channels. The demonstrated resolution is 1,024 × 1,024 pixels at 124 fps. We demonstrated its wide applications, including chlorophyll and sugar quantification for intelligent agriculture, blood oxygen and water quality monitoring for human health, textile classification and apple bruise detection for industrial automation, and remote lunar detection for astronomy. The integrated hyperspectral image sensor weighs only tens of grams and can be assembled on various resource-limited platforms or equipped with off-the-shelf optical systems. The technique transforms the challenge of high-dimensional imaging from a high-cost manufacturing and cumbersome system to one that is solvable through on-chip compression and agile computation.

Mesoscopic axially swept oblique plane microscope for the imaging of freely moving organisms with near-isotropic resolution

Rapid three-dimensional imaging over extended fields of view (FOVs) is crucial to the study of organism-wide systems and biological processes in vivo. Selective-plane illumination microscopy (SPIM) is a powerful method for high spatio-temporal resolution in toto imaging of such biological specimens. However, typical SPIM implementations preclude conventional sample mounting and have anisotropic imaging performance, in particular when designed for large FOVs over 1 mm diameter. Here, we introduce axial sweeping of the illumination into a non-orthogonal dual-objective oblique plane microscope (OPM) design, thereby enabling the observation of freely moving animals over millimeter-sized FOVs, at close to isotropic, sub-cellular resolution. We apply our mesoscopic axially swept OPM (MASOPM) to image the behavioral dynamics of the sea anemone Nematostella vectensis over 1 × 0.7 × 0.4 mm at 1.7 × 2.6 × 3.7 µm resolution and 0.5 Hz volume rate.

Super resolution reconstruction of fluorescence microscopy images by a convolutional network with physical priors

Super-solution fluorescence microscopy, such as single-molecule localization microscopy (SMLM), is effective in observing subcellular structures and achieving excellent enhancement in spatial resolution in contrast to traditional fluorescence microscopy. Recently, deep learning has demonstrated excellent performance in SMLM in solving the trade-offs between spatiotemporal resolution, phototoxicity, and signal intensity. However, most of these researches rely on sufficient and high-quality datasets. Here, we propose a physical priors-based convolutional super-resolution network (PCSR), which incorporates a physical-based loss term and an initial optimization process based on the Wiener filter to create excellent super-resolution images directly using low-resolution images. The experimental results demonstrate that PCSR enables the achievement of a fast reconstruction time of 100 ms and a high spatial resolution of 10 nm by training on a limited dataset, allowing subcellular research with high spatiotemporal resolution, low cell phototoxic illumination, and high accessibility. In addition, the generalizability of PCSR to different live cell structures makes it a practical instrument for diverse cell research.

Elucidating the spatiotemporal dynamics of glucose metabolism with genetically encoded fluorescent biosensors.

Glucose metabolism has been well understood for many years, but some intriguing questions remain regarding the subcellular distribution, transport, and functions of glycolytic metabolites. To address these issues, a living cell metabolic monitoring technology with high spatiotemporal resolution is needed. Genetically encoded fluorescent sensors can achieve specific, sensitive, and spatiotemporally resolved metabolic monitoring in living cells and invivo, and dozens of glucose metabolite sensors have been developed recently. Here, we highlight the importance of tracking specific intermediate metabolites of glycolysis and glycolytic flux measurements, monitoring the spatiotemporal dynamics, and quantifying metabolite abundance. We then describe the working principles of fluorescent protein sensors and summarize the existing biosensors and their application in understanding glucose metabolism. Finally, we analyze the remaining challenges in developing high-quality biosensors and the huge potential of biosensor-based metabolic monitoring at multiple spatiotemporal scales.

Measurement of ocean currents by seafloor distributed optical-fiber acoustic sensing.

Ocean current measurements play a crucial role in aiding our understanding of ocean dynamics and circulation systems. Traditional methods, such as drifters and ocean buoys, are sparsely distributed and of limited effectiveness due to the nature of the marine environment and high operating expenses. Distributed acoustic sensing (DAS) is an emerging technology using submarine optical-fiber (OF) cables as dense seismo-acoustic arrays, offering a new perspective for ocean observations. Here, in situ observations of ocean surface gravity waves (OSGWs) and ocean currents by DAS were made along a pre-existing 33.6 km seafloor OF cable. The average current velocity and water depth along the cable were determined from observed OSGW-induced seafloor noise (0.05-0.2 Hz) using ambient-noise interferometry and frequency-domain beamforming. Variations in current velocity were derived at high spatiotemporal resolution using the frequency-domain waveform-stretching method. The inverted current velocity was verified by nearby ocean buoy observations and forecasting results. The observations demonstrate the effectiveness of DAS-instrumented OF cables in monitoring ocean currents.

MRI and CT compatible asymmetric bilayer hydrogel electrodes for EEG-based brain activity monitoring

The exploration of multi-dimensional brain activity with high temporal and spatial resolution is of great significance in the diagnosis of neurological disease and the study of brain science. Although the integration of electroencephalogram (EEG) with magnetic resonance imaging (MRI) and computed tomography (CT) provides a potential solution to achieve a brain-functional image with high spatiotemporal resolution, the critical issues of interface stability and magnetic compatibility remain challenging. Therefore, in this research, we proposed a conductive hydrogel EEG electrode with an asymmetrical bilayer structure, which shows the potential to overcome the challenges. Benefiting from the bilayer structure with different moduli, the hydrogel electrode exhibits high biological and mechanical compatibility with the heterogeneous brain-electrode interface. As a result, the impedance can be reduced compared with conventional metal electrodes. In addition, the hydrogel-based ionic conductive electrodes, which are free from metal conductors, are compatible with MRI and CT. Therefore, they can obtain high spatiotemporal resolution multi-dimensional brain information in clinical settings. The research outcome provides a new approach for establishing a platform for early diagnosis of brain diseases and the study of brain science.

Artificial Tactile Sensory Finger for Contact Pattern Identification Based on High Spatiotemporal Piezoresistive Sensor Array.

Human fingertip tactile perception relies on the activation of densely distributed tactile receptors to identify contact patterns in the brain. Despite significant efforts to integrate tactile sensors with machine learning algorithms for recognizing physical patterns on object surfaces, developing a tactile sensing system that emulates human fingertip capabilities for identifying contact patterns with a high spatiotemporal resolution remains a formidable challenge. In this study, we present the development of an artificial tactile finger for accurate contact pattern identification, achieved through the integration of a high spatiotemporal piezoresistive sensor array (PRSA) and a convolutional neural network (CNN) model. Spatiotemporal characterization tests reveal that the artificial finger exhibits a fast temporal resolution of approximately 7 ms and achieves a two-point threshold of 1.5 mm, surpassing that of the human fingertip. To compare the performance of the artificial finger with the human finger in recognizing different patterns, we acquired pressure images by pressing the artificial finger, coated with a flexible PRSA film, onto both simple embossed and complex curved patterns while also recording human recognition results of perceiving these patterns. Experimental findings demonstrate that the artificial finger achieves higher classification accuracy in recognizing both simple and complex patterns (99.0 and 96.1%, respectively) compared to the human fingertip (69.1 and 22.7%). This artificial finger serves as a promising platform with great potential for various robotic tactile sensing applications including prosthetics, skin electronics, and robotic surgery.

A Novel Single-Color FRET Sensor for Rho-Kinase Reveals Calcium-Dependent Activation of RhoA and ROCK.

Ras homolog family member A (RhoA) acts as a signaling hub in many cellular processes, including cytoskeletal dynamics, division, migration, and adhesion. RhoA activity is tightly spatiotemporally controlled, but whether downstream effectors share these activation dynamics is unknown. We developed a novel single-color FRET biosensor to measure Rho-associated kinase (ROCK) activity with high spatiotemporal resolution in live cells. We report the validation of the Rho-Kinase Activity Reporter (RhoKAR) biosensor. RhoKAR activation was specific to ROCK activity and was insensitive to PKA activity. We then assessed the mechanisms of ROCK activation in mouse fibroblasts. Increasing intracellular calcium with ionomycin increased RhoKAR activity and depleting intracellular calcium with EGTA decreased RhoKAR activity. We also investigated the signaling intermediates in this process. Blocking calmodulin or CaMKII prevented calcium-dependent activation of ROCK. These results indicate that ROCK activity is increased by calcium in fibroblasts and that this activation occurs downstream of CaM/CaMKII.

Neural mechanisms of fear responses to emotional stimuli: a preliminary study combining early posterior negativity and electroencephalogram source network analysis

Fear emotion is a typical negative emotion that is commonly present in daily life and significantly influences human behavior. A deeper understanding of the mechanisms underlying negative emotions contributes to the improvement of diagnosing and treating disorders related to negative emotions. However, the neural mechanisms of the brain when faced with fearful emotional stimuli remain unclear. To this end, this study further combined electroencephalogram (EEG) source analysis and cortical brain network construction based on early posterior negativity (EPN) analysis to explore the differences in brain information processing mechanisms under fearful and neutral emotional picture stimuli from a spatiotemporal perspective. The results revealed that neutral emotional stimuli could elicit higher EPN amplitudes compared to fearful stimuli. Further source analysis of EEG data containing EPN components revealed significant differences in brain cortical activation areas between fearful and neutral emotional stimuli. Subsequently, more functional connections were observed in the brain network in the alpha frequency band for fearful emotions compared to neutral emotions. By quantifying brain network properties, we found that the average node degree and average clustering coefficient under fearful emotional stimuli were significantly larger compared to neutral emotions. These results indicate that combining EPN analysis with EEG source component and brain network analysis helps to explore brain functional modulation in the processing of fearful emotions with higher spatiotemporal resolution, providing a new perspective on the neural mechanisms of negative emotions.

Investigation of the Structure and Optical Properties of Polymethine-Based NIR-II Fluorophores Using Many-Body Perturbation Theory: GW-BSE Approaches.

Fluorescence imaging is a widely used technique for detecting pathophysiological microenvironments and guiding fluorescence-guided therapy owing to its noninvasiveness, high spatiotemporal resolution, ease of operation, and real-time monitoring capabilities. In particular, NIR-II materials are promising for fluorescence imaging applications because they exhibit reduced light scattering and absorption by biological tissues, enabling deeper imaging with improved spatial resolution and contrast compared to visible or first near-infrared imaging. NIR-II materials refer to those that emit in the second near-infrared region of the electromagnetic spectrum, spanning wavelengths from approximately 1000 to 1700 nm. The emission peaks of organic fluorophores within the NIR-II window are of particular interest due to their minimal biotoxicity, in vivo biocompatibility, and biodegradability. In this study, we investigated a new series of NIR-II fluorescent polymethine-based dyes and their NIR-II absorption properties using density functional theory and the GW-BSE approximation. Our calculated maximum absorption peak under the GW-BSE approximation showed good agreement with experimental results, demonstrating the potential of these dyes for NIR-II fluorescence imaging applications.

High-resolution spatiotemporal forecasting of the European crane migration

In this paper we present three different models to forecast bird migration. They are species-specific individual-based models that operate on a high spatiotemporal resolution (kilometres, 15 min-hours), as an addition to radar-based migration forecast models that currently exist. The models vary in complexity, and use GPS-tracked location, flying direction and speed, and/or wind data to forecast migration speed and direction. Our aim is to quantitatively evaluate the forecasting performance and assess which metrics improve forecasts at different ranges. We test the models through cross-validation using GPS tracks of common cranes during spring and autumn migration. Our results show that recordings of flight speed and direction improve the accuracy of forecasts on the short range (<2 h). Adding wind data at flight altitude results in consistent improvements of the forecasts across the entire range, particularly in the predicted speed. Direction forecasts are less affected by adding wind data because cranes mostly compensate for wind drift during migration. Migration in spring is more difficult to forecast than in autumn, resulting in larger errors in flight speed and direction during spring. We further find that a combination of flight behaviours – thermal soaring, gliding, and flapping – complicates the forecasts by inducing variance in flight speed and direction. Fitting those behaviours into flight optimisation models proves to be challenging, and even results in significant biases in speed forecasts in spring. We conclude that flight speed is the most difficult parameter to forecast, whereas flight direction is the most critical for practical applications of these models. Such applications could e.g., be prevention of bird strikes in aviation or with wind turbines, and public engagement with bird migration.

Elevated endoplasmic reticulum pH is associated with high growth and bisAb aggregation in CHO cells.

Chinese hamster ovary (CHO) bioprocesses, the dominant platform for therapeutic protein production, are increasingly used to produce complex multispecific proteins. Product quantity and quality are affected by intracellular conditions, but these are challenging to measure and often overlooked during process optimization studies. pH is known to impact quality attributes like protein aggregation across upstream and downstream processes, yet the effects of intracellular pH on cell culture performance are largely unknown. Recently, advances in protein biosensors have enabled investigations of intracellular environments with high spatiotemporal resolution. In this study, we integrated a fluorescent pH-sensitive biosensor into a bispecifc (bisAb)-producing cell line to investigate changes in endoplasmic reticulum pH (pHER). We then investigated how changes in lactate metabolism impacted pHER, cellular redox, and product quality in fed-batch and perfusion bioreactors. Our data show pHER rapidly increased during exponential growth to a maximum of pH 7.7, followed by a sharp drop in the stationary phase in all perfusion and fed-batch conditions. pHER decline in the stationary phase was driven by an apparent loss of cellular pH regulation that occurred despite differences in redox profiles. Finally, we found protein aggregate levels correlated most closely with pHER which provides new insights into product aggregate formation in CHO processes. An improved understanding of the intracellular changes impacting bioprocesses can ultimately help guide media optimizations, improve bioprocess control strategies, or provide new targets for cell engineering.

Near-Infrared II Fluorescence Imaging Highlights Tumor Angiogenesis in Hepatocellular Carcinoma with a VEGFR-Targeted Probe.

Hepatocellular carcinoma (HCC) is typically characterized by rich vascularity, with angiogenesis playing a crucial role in its growth and invasion. Molecular imaging of specific receptors in blood vessels is crucial in HCC diagnosis. In particular, in vivo imaging utilizing the second near-infrared (NIR-II) window offers improved tissue penetration, reduced light scattering, and lower autofluorescence. Despite the great potential of the NIR-II window, developing safe and effective probes to provide better imaging performance for HCC is urgently needed. In this study, NIR-II imaging integrated with a vascular endothelial growth factor receptor (VEGFR)-targeted probe generated by combining a VEGFR-targeted peptide with indocyanine green (ICG) is used to characterize HCC-related angiogenesis at a resolution of 56.0µm. For the first time, liver metabolic curves and parameters of liver function reserve (LFR) are obtained by fitting NIR-II fluorescence signals with high spatiotemporal resolution, showing significant differences between HCC mice and controls. Moreover, unlike ICG, the targeting probe has a targeted effect on blood vessels in vivo. The tumor-to-normal (T/N) ratio in NIR-II imaging reaches up to 3.30 after post-injection of the targeting probe. The results indicate that the VEGFR-targeted probe is a powerful tool for NIR-II fluorescence imaging to enhance early diagnosis of HCC.

Ecological change increases malaria risk in the Brazilian Amazon

Ecological change in the Brazilian Amazon is closely linked to human mobility and health. Mining, agriculture, logging, and other activities alter highly diverse ecological and demographic contexts and subsequent exposure to diseases such as malaria. Studies that have attempted to quantify the impact of deforestation on malaria in the Brazilian Amazon have produced conflicting results. However, they varied in methodology and data sources. Most importantly, all studies used annual data, neglecting the subannual seasonal dynamics of malaria. Here, we fill the knowledge gap on the subannual relationship between ecological change in the Brazilian Amazon and malaria transmission. Using the highest spatiotemporal resolution available, we estimated the effect of deforestation on malaria cases between 2003 and 2022 using a stratified Bayesian spatiotemporal hierarchical zero-inflated Poisson model fitted with the Integrated Nested Laplace Approximation. The model was also stratified by state. We found that a 1% increase in 1-mo lagged deforestation increased malaria cases in a given month and municipality by 6.3% [95% credible interval (Crl): 6.2, 6.5%]. Based on an interaction term included in the model, the effect of deforestation on malaria was even larger in areas with higher forest cover. We found that the coefficients for deforestation and mobility were highly variable when stratified by state. Our results provide detailed evidence that, on average, deforestation increases malaria transmission, but that the relationship is not spatiotemporally uniform. These results have implications for stratifying malaria control interventions based on ecological dynamics to help Brazil achieve its goal of malaria elimination by 2035.

Enhanced visualization of quench dynamics of HTS coils through embedded and distributed fiber optical sensing

The development of high-temperature superconducting (HTS) coils and magnets marks a significant advancement across various fields. To ensure their safety and reliability, thorough performance testing under extreme multi-field conditions is essential. This study introduces an innovative method that utilizes embedded and distributed fiber optical sensing (ED-FOS) in HTS pancake coils for precise real-time thermal monitoring and quench visualization. Incorporated during the manufacturing process, the ED-FOS sensors offer comprehensive and distributed measurements of thermal behavior during quenches. Our experiments demonstrate the ED-FOS effectively detects quenches caused by overcurrent and thermal issues. Unlike conventional techniques that rely on global voltage or magnetic field assessments, ED-FOS provides high spatiotemporal resolution and enhances temperature sensitivity. This capability allows for accurate, real-time identification and tracking of quench locations, which is essential for evaluating reliability and safety, as well as for improving performance. This advancement in HTS coil technology paves the way for wider application in critical fields and significantly enhances the design and management of superconducting coils.