Single Particle Analysis Research Articles

Abstract 3633: Multi-parametric characterization of extracellular vesicles in the aqueous humor of uveal melanoma eyes undergoing brachytherapy

Abstract Introduction: Aqueous humor (AH), fluid in the anterior chamber of the eye, is a liquid biopsy source of tumor information in uveal melanoma (UM). Extracellular vesicles (EVs) have recently been characterized in the AH of retinoblastoma eyes, however, have not been investigated in UM. EVs are small membrane-enclosed particles secreted by virtually every cell type with a role in intercellular communications. We hypothesize that tumor-derived EVs are detectable in the AH of UM eyes and that understanding the type of vesicles present may help us better understand their function, particularly for cancer. Small extracellular vesicles (sEVs) have been shown to promote tumorigenesis, treatment resistance, and metastasis, leading to the discovery of clinically-relevant biomarkers for multiple cancer types. As the diversity and role of sEVs in the AH of UM patients has never previously been reported, this project is a first step towards investigating new biomarkers of clinical utility. Our aim is to use single particle analysis to characterize sEV subpopulations in the AH of UM patients by quantifying their size, concentration, and phenotypes based on cell surface markers, specifically tetraspanin co-expression patterns. Methods: sEVs were analyzed from paired pre- and post-brachytherapy AH samples collected from 19 UM patients. AH samples from 5 glaucoma patients served as the control cohort. Unprocessed AH underwent Nanoparticle Tracking Analysis for size quantification and Single Particle-Interferometric Reflectance Imaging Sensor analysis for fluorescent particle count and tetraspanin immunophenotyping; counts were subsequently converted to percentages for analysis. Statistics were performed using Mann-Whitney U, ANOVA, and Tukey’s tests. Results: AH derived from UM eyes (pre-brachytherapy) displayed a broader sEV size distribution than glaucoma eyes, with more diverse sEV subpopulations. Both tumor and nontumor AH samples demonstrated a dominant CD63+ sEV subpopulation. A significantly higher percentage of CD63/81+ sEVs (P= 0.0217) and CD9/63/81+ sEVs (P= 0.0146) were found in post-brachytherapy samples compared to pre-brachytherapy. Conclusions: sEV subpopulations in UM eyes demonstrate increased heterogeneity in comparison to nontumor eyes. Our results are consistent with prior studies reporting that the CD63+ sEV subtype is an AH-specific biomarker enriched across multiple ocular diseases. The increase in CD63/81+ sEVs and CD9/63/81+ sEVs after brachytherapy is presumably a result of radiation-induced release of these vesicles, suggesting a tumor-derived origin of these subpopulations. CD63/81+ sEV subpopulation was previously reported to also be a tumor-derived subpopulation in AH of retinoblastoma eyes. Further study of the cargo carried by these sEV subpopulations may uncover molecular mechanisms pivotal to UM and other ocular cancers. Citation Format: Shreya Sirivolu, Chen-Ching Peng, Paolo Neviani, Jesse L. Berry, Liya Xu. Multi-parametric characterization of extracellular vesicles in the aqueous humor of uveal melanoma eyes undergoing brachytherapy [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 3633.

Analysis of single particle and collective beam effects in high intensity beams in a periodic quadrupole channel

In high intensity proton accelerators, there are two main mechanisms that can cause beam degradation: incoherent and coherent effects due to nonlinear space charge forces. The incoherent effects represent the single particle dynamics while the coherent effects represent the collective response of the beam. Of particular interest is the region above a zero current phase advance (σ0) of 90° where the (coherent) second-order envelope instability and the (incoherent) fourth-order particle resonance are seen to lead to emittance growth. Large emittance growth is also seen below the envelope instability region as the full current beam phase advance (σ) decreases. In the present study, we have studied the nonlinear effects in a high intensity beam propagating through a focusing-defocusing (FD) quadrupole channel for σ0 greater than 90°, both analytically, by studying the solutions of Kapchinsky-Vladimirsky (KV) equation and the particle core model, and through detailed particle-in-cell (PIC) simulations using the code. The KV envelope equation gives the collective response of the beam while the particle core model gives the contribution of the single particle effects. With pic simulations, which resemble the behavior of the real beams more closely as compared to envelope calculations or the particle core model, it is possible to study the evolution of the beam in a self-consistent manner. Our studies show, that it is possible to identify the specific process responsible for beam degradation in high intensity beams. It is also possible to identify which process dominates under different conditions. We further show that the width of the emittance increase stop band calculated from PIC simulations is wider than that calculated by the envelope equations and that the width depends on the length of the channel being studied. Published by the American Physical Society 2024

Learning structural heterogeneity from cryo-electron sub-tomograms with tomoDRGN.

Cryo-electron tomography (cryo-ET) enables observation of macromolecular complexes in their native, spatially contextualized cellular environment. Cryo-ET processing software to visualize such complexes at nanometer resolution via iterative alignment and averaging are well developed but rely upon assumptions of structural homogeneity among the complexes of interest. Recently developed tools allow for some assessment of structural diversity but have limited capacity to represent highly heterogeneous structures, including those undergoing continuous conformational changes. Here we extend the highly expressive cryoDRGN (Deep Reconstructing Generative Networks) deep learning architecture, originally created for single-particle cryo-electron microscopy analysis, to cryo-ET. Our new tool, tomoDRGN, learns a continuous low-dimensional representation of structural heterogeneity in cryo-ET datasets while also learning to reconstruct heterogeneous structural ensembles supported by the underlying data. Using simulated and experimental data, we describe and benchmark architectural choices within tomoDRGN that are uniquely necessitated and enabled by cryo-ET. We additionally illustrate tomoDRGN's efficacy in analyzing diverse datasets, using it to reveal high-level organization of human immunodeficiency virus (HIV) capsid complexes assembled in virus-like particles and to resolve extensive structural heterogeneity among ribosomes imaged in situ.

Chemical composition, sources and formation mechanism of urban PM2.5 in Southwest China: a case study at the beginning of 2023

Abstract. Despite significant improvements in air quality in recent years, the Sichuan Basin (SCB) is still facing frequent haze pollution in winter, and the causes of severe haze formation have not yet been fully investigated. In this study, the chemical components of PM2.5 (i.e., particulate matter with an aerodynamic diameter of less than 2.5 µm) in a typical pollution period at the beginning of 2023 in Chengdu, a megacity in the SCB, were characterized by bulk-chemical and single-particle analysis, and the PM2.5 sources and formation mechanism of pollution were analyzed. The average mass concentration of PM2.5 during the study period was 95.6 ± 28.7 µg m−3. Organic matter (OM) was the most abundant component (35.3 %), followed by nitrate (22.0 %), sulfate (9.2 %) and ammonium (7.8 %). The individual aerosol particles were classified into five categories, i.e., mineral, OM, secondary inorganic aerosol (SIA), soot and fly ash/metal particles, and most of them were in the state of being internally mixed. The entire observation period could be divided into two non-pollution periods (NP-1 and NP-2) and two haze periods (Haze-1 and Haze-2). With the evolution of pollution, the bulk-chemical and single-particle analysis exhibited similar characteristics, suggesting that Haze-1 was mainly caused by pollutants related to fossil fuel combustion, especially local mobile sources, while Haze-2 was triggered by the rapidly increasing secondary pollutants, which mainly came from regional transmission. The PM2.5 sources included dust (8.5 %), biomass burning (3.5 %), coal combustion (15.4 %), industrial processes (6.5 %), vehicular emissions (25.6 %) and secondary sources (40.5 %). Analysis of Weather Research and Forecasting model with Chemistry (WRF-Chem) model results showed that the average contributions of local sources and regional transmission to pollution in Chengdu were the same (50 % vs. 50 %). In addition, the source composition and WRF-Chem simulation results in different periods confirmed our analysis of the formation mechanisms of the two haze events. This study confirms that further significant reductions in PM2.5 in Chengdu are still needed, and more effective policies for local emission reduction or joint prevention and control of regional air pollution will be necessary in the future.

Deep generative priors for biomolecular 3D heterogeneous reconstruction from cryo-EM projections

Cryo-electron microscopy has become a powerful tool to determine three-dimensional (3D) structures of rigid biological macromolecules from noisy micrographs with single-particle reconstruction. Recently, deep neural networks, e.g., CryoDRGN, have demonstrated conformational and compositional heterogeneity of complexes. However, the lack of ground-truth conformations poses a challenge to assess the performance of heterogeneity analysis methods. In this work, variational autoencoders (VAE) with three types of deep generative priors were learned for latent variable inference and heterogeneous 3D reconstruction via Bayesian inference. More specifically, VAEs with “Variational Mixture of Posteriors” priors (VampPrior-SPR), non-parametric exemplar-based priors (ExemplarPrior-SPR) and priors from latent score-based generative models (LSGM-SPR) were quantitatively compared with CryoDRGN. We built four simulated datasets composed of hypothetical continuous conformation or discrete states of the hERG K + channel. Empirical and quantitative comparisons of inferred latent representations were performed with affine-transformation-based metrics. These models with more informative priors gave better regularized, interpretable factorized latent representations with better conserved pairwise distances, less deformed latent distributions and lower within-cluster variances. They were also tested on experimental datasets to resolve compositional and conformational heterogeneity (50S ribosome assembly, cowpea chlorotic mottle virus, and pre-catalytic spliceosome) with comparable high resolution. Codes and data are available: https://github.com/benjamin3344/DGP-SPR.

Accurate nanoparticle size measurement by combining photometry and tracking analysis

Accurate determination of nanoparticle size is paramount in various fields, including molecular imaging, food safety, drug delivery, and nanobiotechnology. Conventional methods face limitations in accurately resolving different size distributions. Here, we introduce an approach to measure size distribution by combining photometry and tracking analysis of single particles. Our approach is based on a plasmonic dark field imaging system to image and track individual nanoparticles. Scattering intensity, spot size, and diffusion coefficient are quantified and fed into the machine learning model to establish the relationship with particle sizes. Compared with conventional methods, our approach shows improved accuracy in size measurement. To verify the universality of our method, we further demonstrate the sizing capability at diverse and complex conditions, enabling us to discriminate particle size differences within 20 nm in polydisperse systems.

Colocalization of protein and microRNA markers reveals unique extracellular vesicle subpopulations for early cancer detection.

Extracellular vesicles (EVs) play important roles in cell-cell communication but are highly heterogeneous, and each vesicle has dimensions smaller than 200 nm with very limited amounts of cargos encapsulated. The technique of NanOstirBar (NOB)-EnabLed Single Particle Analysis (NOBEL-SPA) reported in the present work permits rapid inspection of single EV with high confidence by confocal fluorescence microscopy, thus enables colocalization assessment for selected protein and microRNA (miRNA) markers in the EVs produced by various cell lines, or present in clinical sera samples. EV subpopulations marked by the colocalization of unique protein and miRNA combinations were discovered to be able to detect early-stage (stage I or II) breast cancer (BC). NOBEL-SPA can be adapted to analyze other types of cargo molecules or other small submicron biological particles. Study of the sorting of specific cargos to heterogeneous vesicles under different physiological conditions can help discover distinct vesicle subpopulations valuable in clinical examination and therapeutics development and gain better understanding of their biogenesis.

Cryogenic electron microscopy and tomography reveal imperfect icosahedral symmetry in alphaviruses.

Alphaviruses are spherical, enveloped RNA viruses with two-layered icosahedral architecture. The structures of many alphaviruses have been studied using cryogenic electron microscopy (cryo-EM) reconstructions, which impose icosahedral symmetry on the viral particles. Using cryogenic electron tomography (cryo-ET), we revealed a polarized symmetry defect in the icosahedral lattice of Chikungunya virus (CHIKV) in situ, similar to the late budding particles, suggesting the inherent imperfect symmetry originates from the final pinch-off of assembled virions. We further demonstrated this imperfect symmetry is also present in in vitro purified CHIKV and Mayaro virus, another arthritogenic alphavirus. We employed a subparticle-based single-particle analysis protocol to circumvent the icosahedral imperfection and boosted the resolution of the structure of the CHIKV to ∼3 Å resolution, which revealed detailed molecular interactions between glycoprotein E1-E2 heterodimers in the transmembrane region and multiple lipid-like pocket factors located in a highly conserved hydrophobic pocket. This complementary use of in situ cryo-ET and single-particle cryo-EM approaches provides a more precise structural description of near-icosahedral viruses and valuable insights to guide the development of structure-based antiviral therapies against alphaviruses.

Source Apportionment of PM10 as a Tool for Environmental Sustainability in Three School Districts of Lecce (Apulia)

Air pollution is a great threat to the sustainable development of the world; therefore, the improvement of air quality through the identification and apportionment of emission sources is a significant tool to reach sustainability. Single particle analysis, by means of a scanning electron microscope equipped with X-ray energy dispersive analysis (SEM-EDS), was used to identify the morphological and chemical properties of the PM10 particles in order to identify and quantify the main emission sources in three areas of Lecce, a city in the Apulia region of southern Italy. This type of characterization has not yet been performed for the Lecce site, but it is of particular importance to identify, based on the shape of the particles, the natural sources from the anthropogenic sources that are responsible for the serious health effects of the inhabitants. Three primary schools located in peripheral areas of the city were chosen for the sampling: “School 1” (A site), “School 2” (B site), and “School 3” (C site) to carry out a study of the air quality. The A site is characterized by a greater presence of calcium sulphates probably due both to construction activities present during sampling and to reactions between Ca particles and the sulfur present in the atmosphere. At the C site, there is a relative numerical abundance of different groups of particles that present, in the EDS spectrum, an enrichment in sulfur. At the B site, the number of particle groups is intermediate compared to that of the other two sites. With the source apportionment technique, ten emission sources were identified: combustion, soot, industry, soil, carbonates, sea salt, calcium sulfates, SIA, biological particles, and others. In PM10, the three sites are more affected by the soil source, with an effect greater than 60%.

The application and development of electron microscopy for three-dimensional reconstruction in life science: a review.

Imaging technologies have played a pivotal role in advancing biological research by enabling visualization of biological structures and processes. While traditional electron microscopy (EM) produces two-dimensional images, emerging techniques now allow high-resolution three-dimensional (3D) characterization of specimens in situ, meeting growing needs in molecular and cellular biology. Combining transmission electron microscopy (TEM) with serial sectioning inaugurated 3D imaging, attracting biologists seeking to explore cell ultrastructure and driving advancement of 3D EM reconstruction. By comprehensively and precisely rendering internal structure and distribution, 3D TEM reconstruction provides unparalleled ultrastructural insights into cells and molecules, holding tremendous value for elucidating structure-function relationships and broadly propelling structural biology. Here, we first introduce the principle of 3D reconstruction of cells and tissues by classical approaches in TEM and then discuss modern technologies utilizing TEM and on new SEM-based as well as cryo-electron microscope (cryo-EM) techniques. 3D reconstruction techniques from serial sections, electron tomography (ET), and the recent single-particle analysis (SPA) are examined; the focused ion beam scanning electron microscopy (FIB-SEM), the serial block-face scanning electron microscopy (SBF-SEM), and automatic tape-collecting lathe ultramicrotome (ATUM-SEM) for 3D reconstruction of large volumes are discussed. Finally, we review the challenges and development prospects of these technologies in life science. It aims to provide an informative reference for biological researchers.

Evaluation of methods for characterizing the fine particulate matter emissions from aircraft and other diffusion flame combustion aerosol sources

The U. S. Environmental Protection Agency in collaboration with the U. S. Air Force Arnold Engineering Development Complex conducted the VAriable Response In Aircraft nvPM Testing (VARIAnT) 3 and 4 test campaigns to compare nonvolatile particulate matter (nvPM) emissions measurements from a variety of diffusion flame combustion aerosol sources (DFCASs), including a Cummins diesel engine, a diesel powered generator, two gas turbine start carts, a J85-GE-5 turbojet engine burning multiple fuels, and a Mini-CAST soot generator. The VARIAnT research program was devised to understand reported variability in the ARP6320A sampling system nvPM measurements. The VARIAnT research program has conducted four test campaigns to date with the VARIAnT 3 and 4 campaigns devoted to: (1) assessing the response of three different black carbon mass analyzers to particles of different size, morphology, and chemical composition; (2) characterizing the particles generated by 6 different combustion sources according to morphology, effective density, and chemical composition; and (3) assessing any significant difference between black carbon as determined by the 3 mass analyzers and the total PM determined via other techniques. Results from VARIAnT 3 and 4 campaigns revealed agreement of about 20% between the Micro-Soot Sensor, the Cavity Attenuated Phase Shift (CAPS PMSSA) monitor and the thermal-optical reference method for elemental carbon (EC) mass, independent of the calibration source used. For the LII-300, the measured mass concentrations in VARIAnT 3 fall within 18% and in VARIAnT 4 fall within 27% of the reference EC mass concentration when calibrated on a combustor rig in VARIAnT 3 and on an LGT-60 start cart in VARIAnT 4, respectively. It was also found that the three mass instrument types (MSS, CAPS PMSSA, and LII-300) can exhibit different BC to reference EC ratios depending on the emission source that appear to correlate to particle geometric mean mobility diameter, morphology, or some other parameter associated with particle geometric mean diameter (GMD) with the LII-300 showing a slightly stronger apparent trend with GMD. Systematic differences in LII-300 measured mass concentrations have been reduced by calibrating with a turbine combustion as a particle source (combustor or turbine engine). With respect to the particle size measurements, the sizing instruments (TSI SMPS, TSI EEPS, and Cambustion DMS 500) were found to be in general agreement in terms of size distributions and concentrations with some exceptions. Gravimetric measurements of the total aerosol mass produced by the various DFCAs differed from the reference EC, BC and integrated particle size distribution measured aerosol masses. The measurements of particle size distributions and single particle analysis performed using the miniSPLAT indicated the presence of larger particles (≳150 nm) having more compact morphologies, higher effective density, and a composition dominated by OC and containing ash. This increased large particle fraction is also associated with higher values of single scattering albedo measured by the CAPS PMSSA instrument and higher OC measurements. These measurements indicate gas turbine engine emissions can be a more heterogeneous mix of particle types beyond the original E−31 assumption that engine exit exhaust particles are mainly composed of black carbon.

Extracellular-Vesicle Catch-and-Release Isolation System Using a Net-Charge Invertible Curvature-Sensing Peptide.

Extracellular vesicles (EVs) carry various informative components, including signaling proteins, transcriptional regulators, lipids, and nucleic acids. These components are utilized for cell-cell communication between donor and recipient cells. EVs have shown great promise as pharmaceutical-targeting vesicles and have attracted the attention of researchers in the fields of biological and medical science because of their importance as diagnostic and prognostic markers. However, the isolation and purification of EVs from cell-cultured media remain challenging. Ultracentrifugation is the most widely used method, but it requires specialized and expensive equipment. In the present study, we proposed a novel methodology to isolate EVs using a simple and convenient method, i.e., an EV catch-and-release isolation system (EV-CaRiS) using a net-charge invertible curvature-sensing peptide (NIC). Curvature-sensing peptides recognize vesicles by binding to lipid-packing defects on highly curved membranes regardless of the expression levels of biomarkers. NIC was newly designed to reversibly capture and release EVs in a pH-dependent manner. NIC allowed us to achieve reproducible EV isolation from three human cell lines on resin using a batch method and single-particle imaging of EVs containing the ubiquitous exosome markers CD63 and CD81 by total internal reflection fluorescence microscopy (TIRFM). EV-CaRiS was demonstrated as a simple and convenient methodology for EV isolation, and NIC is promising for applications in the single-particle analysis of EVs.

The α-crystallin Chaperones Undergo a Quasi-ordered Co-aggregation Process in Response to Saturating Client Interaction

Small heat shock proteins (sHSPs) are ATP-independent chaperones vital to cellular proteostasis, preventing protein aggregation events linked to various human diseases including cataract. The α-crystallins, αA-crystallin (αAc) and αB-crystallin (αBc), represent archetypal sHSPs that exhibit complex polydispersed oligomeric assemblies and rapid subunit exchange dynamics. Yet, our understanding of how this plasticity contributes to chaperone function remains poorly understood. Using biochemical and biophysical analyses combined with single-particle electron microscopy (EM), we examined structural changes in αAc, αBc and native heteromeric lens α-crystallins (αLc) in their apo-states and at varying degree of chaperone saturation leading to co-aggregation, using lysozyme and insulin as model clients. Quantitative single-particle analysis unveiled a continuous spectrum of oligomeric states formed during the co-aggregation process, marked by significant client-triggered expansion and quasi-ordered elongation of the sHSP oligomeric scaffold, whereby the native cage-like sHSP assembly displays a directional growth to accommodate saturating conditions of client sequestration. These structural modifications culminated in an apparent amorphous collapse of chaperone-client complexes, resulting in the creation of co-aggregates capable of scattering visible light. Intriguingly, these co-aggregates maintain internal morphological features of highly elongated sHSP oligomers with striking resemblance to polymeric α-crystallin species isolated from aged lens tissue. This mechanism appears consistent across αAc, αBc and αLc, albeit with varying degrees of susceptibility to client-induced co-aggregation. Importantly, our findings suggest that client-induced co-aggregation follows a distinctive mechanistic and quasi-ordered trajectory, distinct from a purely amorphous process. These insights reshape our understanding of the physiological and pathophysiological co-aggregation processes of α-crystallins, carrying potential implications for a pathway toward cataract formation.

Simcryocluster: a semantic similarity clustering method of cryo-EM images by adopting contrastive learning

BackgroundCryo-electron microscopy (Cryo-EM) plays an increasingly important role in the determination of the three-dimensional (3D) structure of macromolecules. In order to achieve 3D reconstruction results close to atomic resolution, 2D single-particle image classification is not only conducive to single-particle selection, but also a key step that affects 3D reconstruction. The main task is to cluster and align 2D single-grain images into non-heterogeneous groups to obtain sharper single-grain images by averaging calculations. The main difficulties are that the cryo-EM single-particle image has a low signal-to-noise ratio (SNR), cannot manually label the data, and the projection direction is random and the distribution is unknown. Therefore, in the low SNR scenario, how to obtain the characteristic information of the effective particles, improve the clustering accuracy, and thus improve the reconstruction accuracy, is a key problem in the 2D image analysis of single particles of cryo-EM.ResultsAiming at the above problems, we propose a learnable deep clustering method and a fast alignment weighted averaging method based on frequency domain space to effectively improve the class averaging results and improve the reconstruction accuracy. In particular, it is very prominent in the feature extraction and dimensionality reduction module. Compared with the classification method based on Bayesian and great likelihood, a large amount of single particle data is required to estimate the relative angle orientation of macromolecular single particles in the 3D structure, and we propose that the clustering method shows good results.ConclusionsSimcryoCluster can use the contrastive learning method to perform well in the unlabeled high-noise cryo-EM single particle image classification task, making it an important tool for cryo-EM protein structure determination

Community recommendations on cryoEM data archiving and validation.

In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for the deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and the resulting consensus recommendations. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.

Thermodynamic solubility measurement without chemical analysis

In this work, the optical imaging based single particle analysis (SPA) and the gold standard shake-flask (SF) solubility methods are compared. We show that to analyze pharmaceutical compounds spanning 7 log units in solubility and a diverse chemical space with limited resources, several analytical techniques are required (HPLC-UV, LC-MS, refractometry and UV–Vis spectrometry), whereas solely the SPA method is able to analyze all the same compounds. SPA experiments take only minutes, while for SF, it may take days to reach thermodynamic equilibration. This decreases the time span needed for the solubility experiment from initial preparations to obtaining the result from roughly three days to less than three hours. The optimal particle size for SPA ranges from approximately one to hundreds of microns. Challenges include measuring large particles, very fast dissolving compounds and handling small sample sizes. Inherent exclusion of density from the SPA measurement is a potential source of error for compounds with very low or high density values. The average relative difference of 37 % between the two methods is very good in the realm of solubility, where 400 % interlaboratory reproducibility can be expected.

African swine fever virus A137R assembles into a dodecahedron cage.

African swine fever (ASF) is a lethal viral disease of pigs caused by African swine fever virus (ASFV). No commercial vaccines and antiviral treatments are available for the prevention and control of the disease. A137R is a structural protein of ASFV that is associated with its virulence. The discovery of the dodecahedron-shaped cage structure of A137R in this study is of great importance in understanding ASFV pathogenicity. This finding sheds light on the molecular mechanisms underlying the functions of A137R. Furthermore, the dodecahedral cage formed by A137R shows promise as a molecular scaffold for nanoparticle vectors. Overall, this study provides valuable insights into the structure and function of A137R, contributing to our understanding of ASFV and potentially opening up new avenues for the development of vaccines or treatments for ASF.

Millennial-scale variability of Greenland dust provenance during the last glacial maximum as determined by single particle analysis

Greenland ice core records exhibited 100-fold higher dust concentrations during the Last Glacial Maximum (LGM) than during the Holocene, and dust input temporal variability corresponded to different climate states in the LGM. While East Asian deserts, the Sahara, and European loess have been suggested as the potential source areas (PSAs) for Greenland LGM dust, millennial-scale variability in their relative contributions within the LGM remains poorly constrained. Here, we present the morphological, mineralogical, and geochemical characteristics of insoluble microparticles to constrain the provenance of dust in Greenland NEEM ice core samples covering cold Greenland Stadials (GS)-2.1a to GS-3 (~ 14.7 to 27.1 kyr ago) in the LGM. The analysis was conducted on individual particles in microdroplet samples by scanning electron microscopy with energy dispersive X-ray spectroscopy and Raman microspectroscopy. We found that the kaolinite-to-chlorite (K/C) ratios and chemical index of alteration (CIA) values were substantially higher (K/C: 1.4 ± 0.7, CIA: 74.7 ± 2.9) during GS-2.1a to 2.1c than during GS-3 (K/C: 0.5 ± 0.1, CIA: 65.8 ± 2.8). Our records revealed a significant increase in Saharan dust contributions from GS-2.1a to GS-2.1c and that the Gobi Desert and/or European loess were potential source(s) during GS-3. This conclusion is further supported by distinctly different carbon contents in particles corresponding to GS-2.1 and GS-3. These results are consistent with previous estimates of proportional dust source contributions obtained using a mixing model based on Pb and Sr isotopic compositions in NEEM LGM ice and indicate millennial-scale changes in Greenland dust provenance that are probably linked to large-scale atmospheric circulation variabilities during the LGM.

A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction.

Cryo-Electron Microscopy (cryo-EM) is a widely used and effective method for determining the three-dimensional (3D) structure of biological molecules. For ab-initio Cryo-EM 3D reconstruction using single particle analysis (SPA), estimating the projection direction of the projection image is a crucial step. However, the existing SPA methods based on common lines are sensitive to noise. The error in common line detection will lead to a poor estimation of the projection directions and thus may greatly affect the final reconstruction results. To improve the reconstruction results, multiple candidate common lines are estimated for each pair of projection images. The key problem then becomes a combination optimization problem of selecting consistent common lines from multiple candidates. To solve the problem efficiently, a physics-inspired method based on a kinetic model is proposed in this work. More specifically, hypothetical attractive forces between each pair of candidate common lines are used to calculate a hypothetical torque exerted on each projection image in the 3D reconstruction space, and the rotation under the hypothetical torque is used to optimize the projection direction estimation of the projection image. This way, the consistent common lines along with the projection directions can be found directly without enumeration of all the combinations of the multiple candidate common lines. Compared with the traditional methods, the proposed method is shown to be able to produce more accurate 3D reconstruction results from high noise projection images. Besides the practical value, the proposed method also serves as a good reference for solving similar combinatorial optimization problems.

Single-Particle Analysis of the Photodegradation of Submicron Polystyrene Particles Using Infrared Photothermal Heterodyne Imaging.

Sunlight irradiation is the predominant process for degrading plastics in the environment, but our current understanding of the degradation of smaller, submicron (<1000 nm) particles is limited due to prior analytical constraints. We used infrared photothermal heterodyne imaging (IR-PHI) to simultaneously analyze the chemical and morphological changes of single polystyrene (PS) particles (∼1000 nm) when exposed to ultraviolet (UV) irradiation (λ = 250-400 nm). Within 6 h of irradiation, infrared bands associated with the backbone of PS decreased, accompanied by a reduction in the particle size. Concurrently, the formation of several spectral features due to photooxidation was attributed to ketones, carboxylic acids, aldehydes, esters, and lactones. Spectral outcomes were used to present an updated reaction scheme for the photodegradation of PS. After 36 h, the average particle size was reduced to 478 ± 158 nm. The rates of size decrease and carbonyl band area increase were -24 ± 3.0 nm h-1 and 2.1 ± 0.6 cm-1 h-1, respectively. Using the size-related rate, we estimated that under peak terrestrial sunlight conditions, it would take less than 500 h for a 1000 nm PS particle to degrade to 1 nm.