Co-located Measurements Research Articles

INF2 mutations cause kidney disease through a gain-of-function mechanism.

Heterozygosity for inverted formin-2 (INF2) mutations causes focal segmental glomerulosclerosis (FSGS) with or without Charcot-Marie-Tooth disease. A key question is whether the disease is caused by gain-of-function effects on INF2 or loss of function (haploinsufficiency). Despite established roles in multiple cellular processes, neither INF2 knockout mice nor mice with a disease-associated point mutation display an evident kidney or neurologic phenotype. Here, we compared responses to puromycin aminonucleoside (PAN)-induced kidney injury between INF2 R218Q and INF2 knockout mice. R218Q INF2 mice are susceptible to glomerular disease, in contrast to INF2 knockout mice. Colocalization, coimmunoprecipitation analyses, and cellular actin measurements showed that INF2 R218Q confers a gain-of-function effect on the actin cytoskeleton. RNA expression analysis showed that adhesion and mitochondria-related pathways were enriched in the PAN-treated R218Q mice. Both podocytes from INF2 R218Q mice and human kidney organoids with an INF2 mutation (S186P) recapitulate adhesion and mitochondrial phenotypes. Thus, gain-of-function mechanisms drive INF2-related FSGS and explain this disease's autosomal dominant inheritance.

Mitochondrial Targetable Turn-On Fluorescent Probe for Fast Detection of NAD(P)H in Living Cells and In Vivo.

Using colorimetric and fluorescent probes has garnered significant interest in detecting NAD(P)H within practical systems and biological organisms. Herein, we synthesized a mitochondrial targetable fluorescent probe (ISQM) for fast NAD(P)H detection in <1 min. The ISQM is positively impacted because of the quinolinium reduction facilitated by NAD(P)H. It consequently liberates the push-pull fluorophore ISQM-H with a large Stokes shift (110 nm). This release leads to a turn-on response of red-emitting fluorescence, accompanied by a meager detection limit of 59 nM. To compare the differences in the NAD(P)H levels of tumor cells and normal cells, we used ISQM to measure the fluorescent signal intensities of HeLa cells (tumor cells) and RAW 264.7 cells (normal cells), respectively. Surprisingly, the experiment, including the measurement of colocalization over time, indicated that the probe exhibits a reaction with mitochondrial NAD(P)H and trace NAD(P)H in hypoxia conditions in cancer cells. Moreover, we effectively used the probe ISQM to identify the NAD(P)H in tumor mice.

Development, Demonstration, and Evaluation of Routine Monitoring of Aerosol Carbon, Oxygen, and Sulfur Content.

Traditional online measurements of the chemical composition of particulate matter have relied on expensive and complex research-grade instrumentation based on mass spectrometry and/or chromatography. However, routine monitoring requires lower-cost alternatives that can be operated autonomously, and such tools are lacking. Routine monitoring of particulate matter, especially organic aerosol, relies instead on offline techniques such as filter collection that require significant operator effort. To address this gap, we present here a new online instrument, the "ChemSpot", that provides information on organic aerosol mass loading, volatility, and degree of oxygenation, along with sulfur content. The instrument grows particles with water condensation, impacts them onto a passivated surface with low heat capacity, and uses stepped thermal desorption of analytes to a combination of flame ionization detector (FID) and flame photometric detector (FPD) and then to a CO2 detector downstream of the FID/FPD setup. By relying on detectors designed for gas chromatography, calibration is achieved almost entirely through the introduction of gases without the need for regular introduction of particle-phase calibrants. Particle collection efficiency of greater than 95% was achieved consistently, and the collection cell was shown to rapidly and precisely heat to ∼800 °C at a rate as fast as 10 °C per second. Measurements of total organic carbon, volatility distribution of organic aerosol, total sulfur, and oxygen-to-carbon ratio (O:C) collected during a continuous multi-week period are presented here to demonstrate the autonomous operation of "ChemSpot". Colocated measurements with a mass spectrometer, an aerosol chemical speciation monitor (ACSM), show good correlation and relatively low bias between the instruments (mean absolute percentage error of 21% and 27% for organic carbon and equivalent sulfate measurements, respectively).

Lusca: FIJI (ImageJ) based tool for automated morphological analysis of cellular and subcellular structures

The human body consists of diverse subcellular, cellular and supracellular structures. Neurons possess varying-sized projections that interact with different cellular structures leading to the development of highly complex morphologies. Aiming to enhance image analysis of complex biological forms including neurons using available FIJI (ImageJ) plugins, Lusca, an advanced open-source tool, was developed. Lusca utilizes machine learning for image segmentation with intensity and size thresholds. It performs particle analysis to ascertain parameters such as area/volume, quantity, and intensity, in addition to skeletonization for determining length, branching, and width. Moreover, in conjunction with colocalization measurements, it provides an extensive set of 29 morphometric parameters for both 2D and 3D analysis. This is a significant enhancement compared to other scripts that offer only 5–15 parameters. Consequently, it ensures quicker and more precise quantification by effectively eliminating noise and discerning subtle details. With three times larger execution speed, fewer false positive and negative results, and the capacity to measure various parameters, Lusca surpasses other existing open-source solutions. Its implementation of machine learning-based segmentation facilitates versatile applications for different cell types and biological structures, including mitochondria, fibres, and vessels. Lusca’s automated and precise measurement capability makes it an ideal choice for diverse biological image analyses.

Abstract 3562: Comparison of spatial co-localization measures for studying the tumor immune microenvironment with application to ovarian cancer

Abstract Introduction: The spatial contexture of the tumor immune microenvironment (TIME) has been associated with survival among cancer patients, including women with high-grade serous ovarian cancer (HGSOC). However, an assessment of statistical approaches to quantify the spatial characteristics of the TIME has not been conducted. Moreover, it is unknown which statistical approach is most sensitive in identifying spatial co-localization of two cell types in the TIME. Methods: Using the R package scSpatialSIM that simulates spatial single-cell protein data (i.e., multiplex immunofluorescence data), we completed a simulation study to compare four methods for assessing co-localization of cell types in the TIME (Ripley’s K, Nearest Neighbor G, Dixon’s segregation statistic, and a spatial interaction variable). The simulation study varied the cell abundance (e.g., low vs high), the co-localization (e.g., co-localization, random, segregation), and the variation in the marked point process. In addition to the simulated data, we assessed the four methods in large epidemiological studies (Nurses’ Health Study [NHSI/NHSII], New England Case Control Study [NECC], African American Cancer Epidemiology Study [AACES], and North Carolina Ovarian Cancer Study [NCOCS]) including 756 women with HGSOC. Multiplex immunofluorescence was conducted using AKOYA Biosciences OPALTM platform to measure cytotoxic T cells (CTLS) and regulatory T cells (Tregs). Cox proportional hazards regression models were fit to estimate the association of spatial co-localization of CTLS and Tregs with overall survival. Results: In the simulation study, we found that Ripley’s K was the most powerful approach for assessing co-localization for a variety of simulation scenarios. Surprisingly, the other approaches (Nearest Neighbor G, Dixon’s Segregation statistic, and spatial interaction statistic) were unable to detect the simulated co-localization of two cell types in most simulation scenarios. In the analysis of women with HGSOC in the epidemiological cohorts, we were able to detect significant co-localization of CTLS and Tregs in 40.2%, 12.2%, 21.2%, and 17.0% of samples using Ripley’s K, Nearest Neighbor G, Dixon’s statistic, and the interaction variable methods, respectively. However, the level of co-localization was not associated with survival. Conclusions: We found that Ripley’s K was the most powerful at detecting simulated co-localization of two cell types in the TIME. Similarly, Ripley’s K identified the highest level of significant spatial co-localization of CTLS and Tregs in the application to HGSOC. However, we did not observe an association of co-localization of CTLS and Tregs with overall survival. Future work is needed to develop powerful approaches for quantifying the spatial contexture of the TIME, along with assessment of the statistical properties of these methods. Citation Format: Brooke L. Fridley, Alex Soupir, Julia Wrobel, Christelle Colin-Leitzinger, Mary K. Townsend, Andrew B. Lawson, Kathryn L. Terry, Joellen M. Schildkraut, Shelley S. Tworoger, Lauren C. Peres. Comparison of spatial co-localization measures for studying the tumor immune microenvironment with application to ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3562.

Output regulation and tracking for linear ODE-hyperbolic PDE–ODE systems

This paper proposes a constructive solution to the output regulation — output tracking problem for a general class of interconnected systems. The class of systems under consideration consists of a linear 2 × 2 hyperbolic Partial Differential Equations (PDE) system coupled at both ends with Ordinary Differential Equations (ODEs). The proximal ODE system, which represents actuator dynamics, is actuated. Colocated measurements are available. The distal ODE system represents the load dynamics. The control objective is to ensure, in the presence of a disturbance signal (regulation problem), that a virtual output exponentially converges to zero. By doing so, we can ensure that a state component of the distal ODE state robustly converges towards a known reference trajectory (output tracking problem) even in the presence of a disturbance with a known structure. The proposed approach combines the backstepping methodology and frequency analysis techniques. We first map the original system to a simpler target system using an invertible integral change of coordinates. From there, we design an adequate full-state feedback controller in the frequency domain. Following a similar approach, we propose a state observer that estimates the state and reconstructs the disturbance from the available measurement. Combining the full-state feedback controller with the state estimation results in a dynamic output-feedback control law. Finally, existing filtering techniques guarantee the closed-loop system robustness properties.

High-resolution repeat topography of drifting ice floes in the Arctic Ocean from terrestrial laser scanning

Snow and ice topography impact and are impacted by fluxes of mass, energy, and momentum in Arctic sea ice. We measured the topography on approximately a 0.5 km2 drifting parcel of Arctic sea ice on 42 separate days from 18 October 2019 to 9 May 2020 via Terrestrial Laser Scanning (TLS). These data are aligned into an ice-fixed, lagrangian reference frame such that topographic changes (e.g., snow accumulation) can be observed for time periods of up to six months. Using in-situ measurements, we have validated the vertical accuracy of the alignment to ± 0.011 m. This data collection and processing workflow is the culmination of several prior measurement campaigns and may be generally applied for repeat TLS measurements on drifting sea ice. We present a description of the data, a software package written to process and align these data, and the philosophy of the data processing. These data can be used to investigate snow accumulation and redistribution, ice dynamics, surface roughness, and they can provide valuable context for co-located measurements.

Commercial kitchen operations produce a diverse range of gas-phase reactive nitrogen species.

Gas-phase reactive nitrogen species (Nr) are important drivers of indoor air quality. Cooking and cleaning are significant direct sources indoors, whose emissions will vary depending on activity and materials used. Commercial kitchens experience regular high volumes of both cooking and cleaning, making them ideal study locations for exploring emission factors from these sources. Here, we present a total Nr (tNr) budget and contributions of key species NO, NO2, acidic Nr (primarily HONO) and basic Nr (primarily NH3) using novel instrumentation in a commercial kitchen over a two-week period. In general, highest tNr was observed in the morning and driven compositionally by NO, indicative of cooking events in the kitchen. The observed HONO and basic Nr levels were unexpectedly stable throughout the day, despite the dynamic and high air change rate in the kitchen. After summing the measured NOx, HONO and Nr,base fractions, there was on average 5 ppbv of Nr unaccounted for, expected to be dominated by neutral Nr species. Using co-located measurements from a proton transfer reaction mass spectrometer (PTR-MS), we propose the identities for these major Nr species from cooking and cleaning that contributed to Nr,base and the neutral fraction of tNr. When focused specifically on cooking events in the kitchen, a vast array of N-containing species was observed by the PTR-MS. Reproducibly, oxygenated N-containing class ions (C1-12H3-24O1-4N1-3), consistent with the known formulae of amides, were observed during meat cooking and may be good cooking tracers. During cleaning, an unexpectedly high level of chloramines was observed, with monochloramine dominating the profile, as emitted directly from HOCl based cleaners or through surface reactions with reduced-N species. For many species within the tNr budget, including HONO, acetonitrile and basic Nr species, we observed stable levels day and night despite the high air change rate during the day (>27 h-1). The stable levels for these species point to large surface reservoirs which act as a significant indoor source, that will be transported outdoors with ventilation.

Can we use X-ray CT to generate 3D penetration resistance data?

Noninvasive imaging of soils with X-ray CT has proven to be a useful method to assess soil structure from a pore space perspective. In contrast, methods like cone penetration tests reflect soil structure from the perspective of the soil matrix as assessed by its mechanical strength. Because both the gray value (GV) obtained with X-ray CT and the penetration resistance (PR) obtained with a cone penetration test depend on soil density there should be a relationship between the two. To the best of our knowledge, no studies attempted so far to investigate the nature of the PR ∼ GV relationship and to understand how well PR and GV are correlated. We aimed at bridging that gap and carried out a combined analysis of local GV and PR with undisturbed soil cores sampled in two soil textures, i.e., loam and sand. To carry out the GV measurements, we developed a new approach which considers an adaptive volume of the zone of influence of the penetrometer tip as a function of soil density. For sand and when looking at samples individually, the correlation between PR and GV was best when the soil microscale heterogeneity was high, i.e., when dense and loose zones of soil were present on the course of the penetrometer tip. For loam, the correlation between PR and GV was not dependent on soil heterogeneity. When looking at the whole dataset, the agreement between PR and GV was better in loam than in sand, with a distance correlation metric of 0.66 for loam and 0.34 for sand, respectively. For loam, the relationship PR ∼ GV had a trend which was similar to that of a hyperbola, i.e., with escalating PR values in a narrow GV range. For sand, no particular model could be recognized. In order to provide a proof-of-concept on how to generate 3D PR maps, the co-located measurements of GV and PR were used to establish an empirical relationship and X-ray CT was used to extrapolate it in 3D. This was carried out with the loam dataset by fitting a hyperbolic function to the PR ∼ GV data pairs. This model was then used to convert GVs into PR values, at a spatial resolution equal to that of the shaft diameter of the penetrometer tip we have used. Notwithstanding the fact that the suggested approach is dependent on numerous experimental conditions and edaphic factors, we advocate for the use of 3D PR maps. These maps could be used in root-soil interactions research, for which the study and breeding of cultivars that could show plastic response in their root systems under mechanical stress is becoming more and more important. This is particularly relevant in the context of mechanized modern agriculture.

Probing Dust and Water in Martian Atmosphere with Far-Infrared Frequency Spacecraft Occultation

Airborne dust plays an active role in determining the thermal structure and chemical composition of the present-day atmosphere of Mars and possibly the planet’s climate evolution over time through radiative–convective and cloud microphysics processes. Thus, accurate measurements of the distribution and variability of dust are required. Observations from the Mars Global Surveyor/Thermal Emission Spectrometer Mars Mars Reconnaissance Orbiter/Mars Climate Sounder and Mars Express/Fourier Transform Spectrometer and the Curiosity Rover have limited capability to measure dust. We show that spacecraft occultation of the Martian atmosphere at far-infrared frequencies between 1 and 10 THz can provide the needed global and temporal data on atmospheric dust by providing co-located measurements of temperature and dust opacity from the top of the atmosphere all the way down to the surface. In addition, spacecraft occultation by a small-satellite constellation could provide global measurements of the development of dust storms.

Adjustment of 1 min rain gauge time series using co-located drop size distribution and wind speed measurements

Abstract. A procedure to adjust rainfall intensity (RI) measurements to account for the wind-induced measurement bias of traditional catching-type gauges is proposed and demonstrated with an application to a suitable case study. The objective is to demonstrate that adjustment curves derived from numerical simulations and disdrometer measurements allow for a posteriori correction of rainfall time series based on the wind velocity measurements alone. To quantify the impact of wind on long-term records, 1 min RI measurements from a cylindrical tipping-bucket rain gauge installed at the Hong Kong Observatory are adjusted. Catch ratios derived from the instrument's aerodynamic behaviour under varying wind speed and drop size combinations are obtained by fitting computational fluid-dynamic simulation results already available in the literature. Co-located high-resolution wind speed measurements from a cup and vane sensor and drop size distribution measurements from an optical video disdrometer (the 2DVD or two-dimensional video disdrometer) are used to infer the collection efficiency of the gauge as a function of wind speed and RI alone and to adjust raw data from a 4-year dataset (2018–2021) of 1 min RI measurements. Due to the specific local climatology, where strong wind is often associated with intense precipitation, 80 % of the dataset adjustments are limited to 4 % of the observed RI values. This, however, results in a significant amount of available freshwater resources that would be missing from the calculated hydrological and water management budget of the region should the adjustments be neglected. This work raises the need to quantify the impact of the wind-induced bias at other sites where disdrometer data support a characterisation of the relationship between the drop size distribution and the measured RI. Depending on the local rain and wind climatology, the correction may account for a significant portion of the annual rainfall amount.

Active vs. passive isotopic analysis: Insights from urban Beijing field measurements and ammonia source signatures

Active collection methods such as ChemComb Speciation Cartridge samplers (CCSCs) are considered more accurate for determining the isotopic composition of NH3 (i.e., δ15N(NH3)), especially in ambient air. However, it is uncertain whether the difference in δ15N values remains consistent when comparing ALPHA to a lab-verified CCSCs with different filter types (Teflon, cellulose, and glass fiber). Here, we deployed two CCSCs and ALPHA side-by-side to collect ambient NH3 samples and compare their δ15N(NH3) values in urban Beijing during July 2019. Furthermore, NH3 source samples from urban traffic and livestock waste were collected using the ALPHA sampler under different scenarios, including various sampling locations, and sampling intervals to assess their representativeness. The results showed that NH3 concentrations measured by ALPHA were 27.6% and 8.5% lower than the concentrations measured by CCSCs A and B, respectively. CCSCs A showed lower δ15N(NH3) values (−16.4 ± 8.0‰) compared to CCSCs B, whereas the δ15N(NH3) values obtained from ALPHA (−23.9 ± 7.7‰) were not significantly different from CCSCs A. This variation in δ15N(NH3) values was attributed to reduced isotopic fractionation (31.5 ± 22.9‰) caused by decreased NH3 volatilization using Teflon and cellulose filter pack configurations. Moreover, this study revealed a consistent 15.1‰ lower δ15N(NH3) value with ALPHA compared to CCSCs B, when Teflon and glass fiber filter pack configurations were used for daily sampling. Additionally, this study revealed that ALPHA sampler might reach saturation when used for longer sampling durations, in contrast to shorter intervals of 8–12 h specifically for livestock waste. This saturation led to positive δ15N(NH3) values (2.9 ± 0.4‰), which were significantly higher compared to samples collected within the 8–12 h range. Further studies should conduct co-located measurements using both passive and active methods, enabling more accurate comparisons of sampling techniques at each location and ensuring representative samples for source apportionment studies.

The EarthCARE mission – science and system overview

Abstract. The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) is a satellite mission implemented by the European Space Agency (ESA), in cooperation with the Japan Aerospace Exploration Agency (JAXA), to measure global profiles of aerosols, clouds and precipitation properties together with radiative fluxes and derived heating rates. The simultaneous measurements of the vertical structure and horizontal distribution of cloud and aerosol fields, together with outgoing radiation, will be used in particular to evaluate their representation in weather forecasting and climate models and to improve our understanding of cloud and aerosol radiative impact and feedback mechanisms. To achieve the objective, the goal is that a retrieved scene with footprint size of 10 km × 10 km is measured with sufficiently high resolution that the atmospheric vertical profile of short-wave (solar) and long-wave (thermal) flux can be reconstructed with an accuracy of 10 W m−2 at the top of the atmosphere. To optimise the performance of the two active instruments, the platform will fly at a relatively low altitude of 393 km, with an equatorial revisit time of 25 d. The scientific payload consists of four instruments: an atmospheric lidar, a cloud-profiling radar with Doppler capability, a multi-spectral imager and a broadband radiometer. Co-located measurements from these instruments are processed in the ground segment, which produces and distributes a wide range of science data products. As well as the Level 1 (L1) product of each instrument, a large number of multiple-instrument L2 products have been developed, in both Europe and Japan, benefiting from the data synergy. An end-to-end simulator and several test scenes have been developed that simulate EarthCARE observations and provide a development and test environment for L1 and L2 processors. Within this paper the EarthCARE observational requirements are addressed. An overview is given of the space segment with a detailed description of the four science instruments, demonstrating how the observational requirements will be met. Furthermore, the elements of the space segment and ground segment that are relevant for science data users are described and the data products are introduced.

Towards a better understanding of fine PM sources: Online and offline datasets combination in a single PMF

Source apportionment (SA) techniques allocate the measured ambient pollutants with their potential source origin; thus, they are a powerful tool for designing air pollution mitigation strategies. Positive Matrix Factorization (PMF) is one of the most widely used SA approaches, and its multi-time resolution (MTR) methodology, which enables mixing different instrument data in their original time resolution, was the focus of this study. One year of co-located measurements in Barcelona, Spain, of non-refractory submicronic particulate matter (NR-PM1), black carbon (BC) and metals were obtained by a Q-ACSM (Aerodyne Research Inc.), an aethalometer (Aerosol d.o.o.) and fine offline quartz-fibre filters, respectively. These data were combined in a MTR PMF analysis preserving the high time resolution (30 min for the NR-PM1 and BC, and 24 h every 4th day for the offline samples). The MTR-PMF outcomes were assessed varying the time resolution of the high-resolution data subset and exploring the error weightings of both subsets. The time resolution assessment revealed that averaging the high-resolution data was disadvantageous in terms of model residuals and environmental interpretability. The MTR-PMF resolved eight PM1 sources: ammonium sulphate + heavy oil combustion (25%), ammonium nitrate + ammonium chloride (17%), aged secondary organic aerosol (SOA) (16%), traffic (14%), biomass burning (9%), fresh SOA (8%), cooking-like organic aerosol (5%), and industry (4%). The MTR-PMF technique identified two more sources relative to the 24 h base case data subset using the same species and four more with respect to the pseudo-conventional approach mimicking offline PMF, indicating that the combination of both high and low TR data is significantly beneficial for SA. Besides the higher number of sources, the MTR-PMF technique has enabled some sources disentanglement compared to the pseudo-conventional and base case PMF as well as the characterisation of their intra-day patterns.

Real-Time Rock-Properties Estimation for Geosteering: Statistical Rock-Physics-Driven Inversion of Seismic Acoustic Impedance and LWD Ultradeep Azimuthal Resistivity

Summary This work describes a statistical rock-physics-driven inversion of seismic acoustic impedance (AI) and ultradeep azimuthal resistivity (UDAR) log data, acquired while drilling, to estimate porosity, water saturation, and facies classes around the wellbore. Despite their limited resolution, seismic data integrated with electromagnetic resistivity log measurements improve the description of rock properties by considering the coupled effects of pore space and fluid saturation in the joint acoustic and electrical domains. The proposed inversion does not explicitly use a forward model, rather the correlation between the petrophysical properties and the resulting geophysical responses is inferred probabilistically from a training data set. The training set is generated by combining available borehole information with a statistical rock-physics modeling approach. In the inversion process, given colocated measurements of seismic AI and logging-while-drilling (LWD) electromagnetic resistivity data, the pointwise probability distribution of rock properties is derived directly from the training data set by applying the kernel density estimation (KDE) algorithm. A nonparametric statistical approach is used to approximate nonsymmetric volumetric distributions of petrophysical properties and to consider the characteristic nonlinear relationship linking water saturation with resistivity. Given an a priori facies classification template for the samples in the training set, it is possible to model the multimodal, facies-dependent behavior of the petrophysical properties, together with their distinctive correlation patterns. A facies-dependent parameterization allows the effect of lithology on acoustic and resistivity responses to be implicitly considered, even though the target properties of inversion are only porosity and saturation. To provide a realistic uncertainty quantification of the estimated rock properties, a plain Bayesian framework is described to account for rock-physics modeling error and to propagate seismic and resistivity data uncertainties to the inversion results. In this respect, the uncertainty related to the scale difference among the well-log data and seismic is addressed by adopting a scale reconciliation strategy. The main feature of the described inversion lies in its fast implementation based on a look-up table that allows rock properties, with their associated uncertainty, to be estimated in real time following the acquisition and inversion of UDAR data. This gives a robust, straightforward, and fast approach that can be effortlessly integrated into existing workflows to support geosteering operations. The inversion is validated on a clastic oil-bearing reservoir, where geosteering was used to guide the placement of a horizontal appraisal well in a complex structural setting. The results show that the proposed methodology provides realistic estimates of the rock-property distributions around the wellbore to depths of investigation of 50 m. These constitute useful information to drive geosteering decisions and can also be used, post-drilling, to update or optimize existing reservoir models.

A comprehensive method to study the DNA's association with lamin and chromatin compaction in intact cell nuclei at super resolution.

Super-resolution fluorescence microscopy has revolutionized multicolor imaging of nuclear structures due to the combination of high labeling specificity and high resolution. Here we expanded the recently developed fBALM (DNA structure fluctuation-assisted binding activated localization microscopy) method by developing a stable methodological sequence that enables dual-color imaging of high-resolution genomic DNA together with an immunofluorescently labeled intranuclear protein. Our measurements of the nuclear periphery, imaging DNA and LaminB1 in biologically relevant samples, show that this novel dual-color imaging method is feasible for further quantitative evaluations. We were able to study the relative spatial signal organization between DNA and LaminB1 by means of highly specific colocalization measurements at nanometer resolution. Measurements were performed with and without the antifade embedding medium ProLong Gold, which proved to be essential for imaging of LaminB1, but not for imaging of SytoxOrange labeled DNA. The localization precision was used to differentiate between localizations with higher and lower amounts of emitting photons. We interpret high intensity localizations to be renatured DNA sections in which a high amount of Sytox Orange molecules were bound. This could give insight into the denaturation kinetics of DNA during fBALM. These results were further complemented by measurements of γH2AX and H3K9me3 signal organization to demonstrate differences within the chromatin landscape, which were quantified with image processing methods such as Voronoi segmentation.

Global burned area mapping from Sentinel-3 Synergy and VIIRS active fires

After more than two decades of successful provision of global burned area data the MODIS mission is near to its end. Therefore, using alternative images to generate moderate resolution burned area maps becomes critical to guarantee temporal continuity of these products. This paper presents the development of a hybrid algorithm based on Copernicus Sentinel-3 (S3) Synergy (SYN) data and Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fires for global detection of burned areas. Using the synergistic and co-located measurements of OLCI and SLSTR instruments on board S3A and S3B, the SYN product offers global, near-daily surface reflectance data at 300 m for both sensors. Our algorithm relied on SYN shortwave infrared (SWIR) bands to compute a multi-temporal separability index that enhanced the burn signal. Active fires from the VIIRS sensor were used to generate spatio-temporal clusters for determining local detection thresholds. Active fires were filtered from those thresholds to obtain the seeds from which a contextual growing was applied to extract burned patches. The algorithm was processed globally for 2019 data to generate a new burned area product, named FireCCIS310. Based on a stratified random sampling, error estimates showed an important reduction of omission errors versus other global burned area products while keeping the commission errors at a similar level (Oe = 41.2% ± 3.0%, Ce = 19.2% ± 1.7%). The new FireCCIS310 dataset included 4.99 million km2 for the year 2019, which implied around 1 million more than the precursor FireCCI51 product, based on MODIS 250 m reflectance values. Temporal reporting accuracy was improved as well, detecting 53% of the burned pixels within a 0–1 day difference. Besides, the new product was much less affected by the border effects than FireCCI51, as a result of an improved active fire filtering process. The FireCCIS310 product is accessible through the CCI Open Data Portal (https://climate.esa.int/es/odp/#/dashboard, last accessed on July 2022).

CO2 in Beijing and Xianghe Observed by Ground-Based FTIR Column Measurements and Validation to OCO-2/3 Satellite Observations

Monitoring the atmospheric CO2 columns inside and around a city is of great importance to understand the temporal–spatial variation of XCO2 near strong anthropogenic emissions. In this study, we use two FTIR CO2 column measurements in Beijing (Bruker EM27/SUN) and Xianghe (Bruker IFS 125HR) between 2019 and 2021 to investigate the differences of XCO2 between Beijing (urban) and Xianghe (suburb) in North China and to validate the OCO-2 and OCO-3 satellite XCO2 retrievals. The mean and standard deviation (std) of the ΔXCO2 between Beijing and Xianghe (Beijing–Xianghe) observed by two FTIR instruments are 0.206 ± 1.736 ppm, which has a seasonal variation and varies with meteorological conditions (wind speed and wind direction). The mean and std of the XCO2 differences between co-located satellite and FTIR measurements are −0.216 ± 1.578 ppm in Beijing and −0.343 ± 1.438 ppm in Xianghe for OCO-2 and 0.637 ± 1.594 ppm in Beijing and 1.206 ± 1.420 ppm in Xianghe for OCO-3. It is found that the OCO-3 snapshot area mode (SAM) measurements can capture the spatial gradient of XCO2 between urban and suburbs well. However, the FTIR measurements indicate that the OCO-3 SAM measurements are about 0.9–1.4 ppm overestimated in Beijing and Xianghe.

Characterization of sub-pollen particles in size-resolved atmospheric aerosol using chemical tracers.

Pollen grains may contain allergens that exacerbate allergic respiratory diseases like asthma and rhinitis. In the presence of water, pollen grains (10–100 μm) can rupture to produce sub-pollen particles (SPP) with diameters <2.5 μm, which in comparison to intact pollen grains, have longer atmospheric lifetimes and greater penetration to the lower lung. The current study examines SPP, fungal spores, and bacteria in size-resolved atmospheric particulate matter (PM) using chemical and biological tracers. During springtime tree pollen season in Iowa City, Iowa, fine particle (PM2.5) concentrations of fructose (a pollen chemical tracer) increased on rainy sampling periods, especially during severe thunderstorms, and peaked when a tornado struck nearby. Submicron fluorescent particles, measured by single-particle fluorescence spectroscopy, were also enhanced during rain events, particularly thunderstorms in agreement with the chemical tracer measurements. PM2.5 sucrose (a pollen chemical tracer) concentrations were higher in early spring when nighttime temperatures were closer to freezing, while fructose concentrations were higher in late spring with warmer temperatures, consistent with chemical tracers being sensitive to seasonal temperature influences. The first co-located measurements of fructose and Bet v 1 (birch pollen allergen), indicated that SPP ranged in diameter from <0.25 to 2.5 μm during rainy sampling periods and that allergens and carbohydrates exhibited distinct size distributions. Meanwhile, mannitol (a fungal spore tracer) peaked on warm, dry days following rain and was primarily in supermicron particles (>1.0 μm), which is consistent with intact fungal spore diameters (1–30 μm). Bacterial endotoxins in PM also increased during extreme weather events, primarily in supermicron particles. While the concentrations of fructose, mannitol, and endotoxin all increased in PM2.5 μm during thunderstorms, the greatest relative increase in concentration was observed for fructose. Together, these observations suggest that SPP containing starch granules and allergens (Bet v 1) were released during rainy sampling periods. This study advances the use of chemical tracers to track SPP and other bioaerosols in the atmosphere, by providing new insight to their size distribution and response to extreme weather conditions.

Canopy-Level Flux and Vertical Gradients of Hg0 Stable Isotopes in Remote Evergreen Broadleaf Forest Show Year-Around Net Hg0 Deposition.

Vegetation uptake represents the dominant route of Hg input to terrestrial ecosystems. However, this plant-directed sink is poorly constrained due to the challenges in measuring the net Hg0 exchange on the ecosystem scale over a long period. Particularly important is the contribution in the subtropics/tropics, where the bulk (∼70%) of the Hg0 deposition is considered to occur. Using the relaxed eddy accumulation technique, this study presents for the first time a whole ecosystem Hg0 flux record over an evergreen hardwood forest. This tower-based micrometeorological method gauged a cumulated net Hg0 flux of -41.1 μg m-2 over 16 months, suggesting that the subtropical montane forest acts as a large and continuous sink of atmospheric Hg0. The monthly net fluxes were consistently negative (-7.3 to -1.0 μg m-2 month-1) throughout the year, with the smallest absolute values occurring during the mild and dry subseason in spring, which was also the annual lowest in vegetation activity. Colocated measurements of multilevel gradients of Hg0 concentration and its stable isotopic composition support the finding of year-round Hg0 deposition. The stable Hg isotope measurements also show that in-canopy bi-directional Hg0 exchange is prevalent.