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Studying specific subpopulations of cancer-derived extracellular vesicles (EVs) could help reveal their role in cancer progression. In cancer, an increase in reactive oxygen species (ROS) happens which results in lipid peroxidation with a major product of 4-hydroxynonenal (HNE). Adduction by HNE causes alteration to the structure of proteins, leading to loss of function. Blebbing of EVs carrying these HNE-adducted proteins as a cargo or carrying HNE-adducted on EV membrane are methods for clearing these molecules by the cells. We have referred to these EVs as Redox EVs. Here, we utilize a surface tension-mediated extraction process, termed exclusion-based sample preparation (ESP), for the rapid and efficient isolation of intact Redox EVs, from a mixed population of EVs derived from human glioblastoma cell line LN18. After optimizing different parameters, two populations of EVs were analyzed, those isolated from the sample (Redox EVs) and those remaining in the original sample (Remaining EVs). Electron microscopic imaging was used to confirm the presence of HNE adducts on the outer leaflet of Redox EVs. Moreover, the population of HNE-adducted Redox EVs shows significantly different characteristics to those of Remaining EVs including smaller size EVs and a more negative zeta potential EVs. We further treated glioblastoma cells (LN18), radiation-resistant glioblastoma cells (RR-LN18), and normal human astrocytes (NHA) with both Remaining and Redox EV populations. Our results indicate that Redox EVs promote the growth of glioblastoma cells, likely through the production of H2O2, and cause injury to normal astrocytes. In contrast, Remaining EVs have minimal impact on the viability of both glioblastoma cells and NHA cells. Thus, isolating a subpopulation of EVs employing ESP-based immunoaffinity could pave the way for a deeper mechanistic understanding of how subtypes of EVs, such as those containing HNE-adducted proteins, induce biological changes in the cells that take up these EVs. 

Abstract. Subarctic cities notoriously experience severe winter pollution episodes with fine particle (PM2.5) concentrations above 35 µg m−3, the US Environmental Protection Agency (EPA) 24 h standard. While winter sources of primary particles in Fairbanks, Alaska, have been studied, the chemistry driving secondary particle formation is elusive. Biomass burning is a major source of wintertime primary particles, making the PM2.5 rich in light-absorbing brown carbon (BrC). When BrC absorbs sunlight, it produces photooxidants – reactive species potentially important for secondary sulfate and secondary organic aerosol formation – yet photooxidant measurements in high-latitude PM2.5 remain scarce. During the winter of 2022 Alaskan Layered Pollution And Chemical Analysis (ALPACA) field campaign in Fairbanks, we collected PM filters, extracted the filters into water, and exposed the extracts to simulated sunlight to characterize the production of three photooxidants: oxidizing triplet excited states of BrC, singlet molecular oxygen, and hydroxyl radical. Next, we used our measurements to model photooxidant production in highly concentrated aerosol liquid water. While conventional wisdom indicates photochemistry is limited during high-latitude winters, we find that BrC photochemistry is significant: we predict high triplet and singlet oxygen daytime particle concentrations up to 2×10-12 and 3×10-11 M, respectively, with moderate hydroxyl radical concentrations up to 5×10-15 M. Although our modeling predicts that triplets account for 0.4 %–10 % of daytime secondary sulfate formation, particle photochemistry cumulatively dominates, generating 76 % of daytime secondary sulfate formation, largely due to in-particle hydrogen peroxide, which contributes 25 %–54 %. Finally, we estimate triplet production rates year-round, revealing the highest rates in late winter when Fairbanks experiences severe pollution and in summer when wildfires generate BrC. 

Fairbanks-North Star Borough, Alaska (FNSB) regularly experiences some of the worst wintertime air quality in the United States. 

Brown carbon (BrC) plays an important role in global radiative budget but there have been few studies on BrC in Arctic despite rapid warming and increasing wildfires in this region. Here we investigate the optical properties of BrC from boreal fires in Alaska summer, with two sets of measurements from PILS-LWCC-TOC (Particle-Into-Liquid-Sampler – Liquid-Waveguide Capillary flow-through optical Cell - Total-Organic-Carbon analyzer) and filter measurements. We show that during intense wildfires, the mass absorption coefficient at 365 nm (MAC365) from water soluble organic carbon (WSOC) remained stable at ∼1 m2 g−1. With all plumes sampled and derived transport time, we show a decrease of MAC365 with plume age, with a shorter photobleaching lifetime (∼11 h) at 365 nm compared to 405 nm (∼20 h). The total absorption by organic aerosols measured from filters at 365 nm is higher than the absorption by WSOC by a factor 2–3, suggesting a dominant role of insoluble organic carbon. Overall BrC dominates absorption in the near-ultraviolet and visible radiation during wildfire season in Alaska summer. 

The prevailing view for aqueous secondary aerosol formation is that it occurs in clouds and fogs, owing to the large liquid water content compared to minute levels in fine particles. Our research indicates that this view may need reevaluation due to enhancements in aqueous reactions in highly concentrated small particles. Here, we show that low temperature can play a role through a unique effect on particle pH that can substantially modulate secondary aerosol formation. Marked increases in hydroxymethanesulfonate observed under extreme cold in Fairbanks, Alaska, demonstrate the effect. These findings provide insight on aqueous chemistry in fine particles under cold conditions expanding possible regions of secondary aerosol formation that are pH dependent beyond conditions of high liquid water. 

Although multiple efforts have been made to model global navigation satellite system (GNSS)-reflectometry (GNSS-R) delay-Doppler maps (DDMs) over land, there is still a need for models that better represent the signals over land and can enable reliable retrievals of the geophysical variables. Our paper presents improvements to an existing GNSS-R DDM model by accounting for short-wave diffraction due to small-scale ground surface roughness and signal attenuation due to vegetation. This is a step forward in increasing the model fidelity. Our model, called the improved geometric optics with topography (IGOT), predicts GNSS-R DDM over land for the purpose of retrieving geophysical parameters, including soil moisture. Validation of the model is carried out using DDMs from the Cyclone GNSS (CYGNSS) mission over two validation sites with in situ soil moisture sensors: Walnut Gulch, AZ, USA, and the Jornada Experimental Range, NM, USA. Both the peak reflectivity and the DDM shape are studied. The results of the study show that the IGOT model is able to accurately predict CYGNSS DDMs at these two validation sites.