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The cycling of atmospheric aerosols through clouds can change their chemical and physical properties and thus modify how aerosols affect cloud microphysics and, subsequently, precipitation and climate. Current knowledge about aerosol processing by clouds is rather limited to chemical reactions within water droplets in warm low-altitude clouds. However, in cold high-altitude cirrus clouds and anvils of high convective clouds in the tropics and midlatitudes, humidified aerosols freeze to form ice, which upon exposure to subsaturation conditions with respect to ice can sublimate, leaving behind residual modified aerosols. This freeze-drying process can occur in various types of clouds. Here we simulate an atmospheric freeze-drying cycle of aerosols in laboratory experiments using proxies for atmospheric aerosols. We find that aerosols that contain organic material that undergo such a process can form highly porous aerosol particles with a larger diameter and a lower density than the initial homogeneous aerosol. We attribute this morphology change to phase separation upon freezing followed by a glass transition of the organic material that can preserve a porous structure after ice sublimation. A porous structure may explain the previously observed enhancement in ice nucleation efficiency of glassy organic particles. We find that highly porous aerosol particles scatter solor light less efficiently than nonporous aerosol particles. Using a combination of satellite and radiosonde data, we show that highly porous aerosol formation can readily occur in highly convective clouds, which are widespread in the tropics and midlatitudes. These observations may have implications for subsequent cloud formation cycles and aerosol albedo near cloud edges.

Biomass burning aerosol is a major source of PM2.5, and significantly affects Earth's radiative budget. The magnitude of its radiative effect is poorly quantified due to uncertainty in the optical properties of aerosol formed from biomass burning. Using a broadband cavity-enhanced spectrometer with a recently increased spectral range (360–720 nm) coupled to a size-selecting aerosol inlet, we retrieve complex refractive indices of aerosol throughout the near-ultraviolet and visible spectral region. We demonstrate refractive index retrievals for two standard aerosol samples: polystyrene latex spheres and ammonium sulfate. We then retrieve refractive indices for biomass burning aerosol from 13 controlled fires during the 2016 Missoula Fire Science Laboratory Study. We demonstrate that the technique is highly sensitive to the accuracy of the aerosol size distribution method and find that while we can constrain the optical properties of brown carbon aerosol for many fires, fresh smoke dominated by fractal-like black carbon aerosol presents unique challenges and is not well-represented by Mie theory. For the 13 fires, we show that the accuracy of Mie theory retrievals decreases as the fraction of black carbon mass increases. At 475 nm, the average refractive index is 1.635 (±0.056) +0.06 (±0.12)i, and at 365 nm, the average refractive index is 1.605 (±0.041) +0.038 (±0.074)i.

Credible climate change predictions require reliable fundamental scientific knowledge of the underlying processes. Despite extensive observational data accumulated to date, atmospheric aerosols still pose key uncertainties in the understanding of Earth’s radiative balance due to direct interaction with radiation and because they modify clouds’ properties. Specifically, major gaps exist in the understanding of the physicochemical pathways that lead to aerosol growth in the atmosphere and to changes in their properties while in the atmosphere. Traditionally, the driving forces for particle growth are attributed to condensation of low vapor pressure species following atmospheric oxidation of volatile compounds by gaseous oxidants. The current study presents experimental evidence of an unaccounted-for new photoinduced pathway for particle growth. We show that heterogeneous reactions activated by light can lead to fast uptake of noncondensable Volatile Organic Compounds (VOCs) at the surface of particles when only traces of a photosensitizer are present in the seed aerosol. Under such conditions, size and mass increase; changes in the chemical composition of the aerosol are also observed upon exposure to volatile organic compounds such as terpenes and near-UV irradiation. Experimentally determined growth rate values match field observations, suggesting that this photochemical process can provide a new, unaccounted-for pathway for atmospheric particle growth and should be considered by models.

Particle morphology is an important parameter affecting aerosol optical properties that are relevant to climate and air quality, yet it is poorly constrained due to sparse in situ measurements. Biomass burning is a large source of aerosol that generates particles with different morphologies. Quantifying the optical contributions of non-spherical aerosol populations is critical for accurate radiative transfer models, and for correctly interpreting remote sensing data. We deployed a laser imaging nephelometer at the Missoula Fire Sciences Laboratory to sample biomass burning aerosol from controlled fires during the FIREX intensive laboratory study. The laser imaging nephelometer measures the unpolarized scattering phase function of an aerosol ensemble using diode lasers at 375 and 405 nm. Scattered light from the bulk aerosol in the instrument is imaged onto a charge-coupled device (CCD) using a wide-angle field-of-view lens, which allows for measurements at 4–175∘ scattering angle with ∼ 0.5∘ angular resolution. Along with a suite of other instruments, the laser imaging nephelometer sampled fresh smoke emissions both directly and after removal of volatile components with a thermodenuder at 250 ∘C. The total integrated aerosol scattering signal agreed with both a cavity ring-down photoacoustic spectrometer system and a traditional integrating nephelometer within instrumental uncertainties. We compare the measured scattering phase functions at 405 nm to theoretical models for spherical (Mie) and fractal (Rayleigh–Debye–Gans) particle morphologies based on the size distribution reported by an optical particle counter. Results from representative fires demonstrate that particle morphology can vary dramatically for different fuel types. In some cases, the measured phase function cannot be described using Mie theory. This study demonstrates the capabilities of the laser imaging nephelometer instrument to provide realtime, in situ information about dominant particle morphology, which is vital for understanding remote sensing data and accurately describing the aerosol population in radiative transfer calculations.

Natural and anthropogenic disasters are associated with air quality concerns due to the potential redistribution of pollutants in the environment. Our objective was to conduct a spatiotemporal analysis of air concentrations of benzene, toluene, ethylbenzne, and xylene (BTEX) and criteria air pollutants in North Carolina during and after Hurricane Florence. Three sampling campaigns were carried out immediately after the storm (September 2018) and at four-month intervals. BTEX were measured along major roads. Concurrent criteria air pollutant concentrations were predicted from modeling. Correlation between air pollutants and possible point sources was conducted using spatial regression. Exceedances of ambient air criteria were observed for benzene (in all sampling periods) and PM2.5 (mostly immediately after Florence). For both, there was an association between higher concentrations and fueling stations, particularly immediately after Florence. For other pollutants, concentrations were generally below levels of regulatory concern. Through characterization of air quality under both disaster and “normal” conditions, this study demonstrates spatial and temporal variation in air pollutants. We found that only benzene and PM2.5 were present at levels of potential concern, and there were localized increases immediately after the hurricane. These substances warrant particular attention in future disaster response research (DR2) investigations.

Lizzie Borden is a legendary figure in American culture who, unlike some others, has not received much scholarly attention. Yet her story has generated a great number and variety of texts, and several performance pieces as well. New texts continue to be published. This body of work begs to be examined, so that insights may be gained into the interactions of popular literacies and narrative forms. The study of different textual treatments of the same subject allows us to trace issues of gender, class, family, the construction of subjectivity, and the intersections of genre, narrative and history. The theoretical approach is presented in the introduction. It draws on a range of perspectives, from feminist, new historicist, and poststructuralist, to biography, genre, film and media, and folklore studies, and from the ideas of Mikhail Bakhtin. An attempt to see how popular texts produce social knowledge requires such an interdisciplinary approach. These theories act as lenses through which the many representations of Lizzie over a century can be viewed and analyzed for their significance. The study is genre-centered, with chapters on biographical texts, journalism, and \"creative\" texts such as novels, short stories, poems, plays, and a television film. Each form is described and explored for its characteristics and how it creates or recreates this legendary figure. One of the most striking features that emerges from this close reading of a century of Borden texts is their level of complexity. One might suppose that there is not much substance to Lizzie Borden, a pop culture icon immortalized in a rhyme, but the texts prove otherwise. They are marked by intertextuality; they borrow from each other, speak to each other, help to shape each other. They also construct readers, and readers construct them. Each text bears the traces of its time. In it are implicated specific cultural concerns and anxieties which tell as much (and sometimes more) about that particular society as about Lizzie Borden. Thus, the study of popular texts can be as rich and revealing as that which focuses on more conventional, canonical literary works.

Older adults are at increased risk of pneumococcal disease. This work aims to evaluate whether there is any decrease in serum IgG against variants of the antigens Pneumococcal surface protein A (PspA) and Pneumococcal surface protein C (PspC) in healthy adults with increasing age. Levels of IgG against PspA and PspC variants were determined by ELISA in serum samples comparing volunteers 18–30 years of age with volunteers who were 50–70+ before and after an experimental pneumococcal colonization challenge. The serotype 6B strain used in the challenge belongs to a minor group of pneumococcal isolates expressing two PspC variants. There was a decrease in levels of IgG with increasing age for the most common PspA variants and for all PspC variants analyzed. No correlation was found between basal levels of IgG against these antigens and protection against colonization. There was an increase in levels of IgG against PspA variants that are more cross-reactive with the variant expressed by the challenge strain post challenge in younger individuals who became colonized. Since the challenge strain used in our study expresses two different PspC variants, an increase in serum IgG against all PspC variants tested was observed in younger individuals who became colonized. For some of the antigen variants tested, a decrease in serum IgG was observed in young volunteers who were challenged but did not become colonized. Serum IgG antibodies against PspA and PspC variants thus decrease with age in healthy adults, but there is no correlation between levels of IgG against these antigens and protection against human experimental colonization. Though no correlation between naturally induced serum IgG antibodies against PspA and PspC and protection against colonization was observed, these results do not rule out the protective potential of these antigens as vaccines against pneumococcal infections.

Qualified Clinical Data Registries (QCDRs) have proliferated across many medical specialties, facilitating quality measure performance monitoring and reporting in programs like the CMS Merit-based Incentive Payment System. Many of these QCDRs offer web-based, clinician-facing dashboards to support quality improvement. However, it is unknown whether engagement with such dashboards is associated with improvements in quality of care. We investigated the cross-sectional relationship between engagement with a QCDR dashboard and quality measure performance. Data derived from a rheumatology QCDR (\"Rheumatology Informatics System for Effectiveness [RISE]\") and audit log data from the dashboard (exposure) and Merit-based Incentive Payment System submission data (outcome) from 2020-2022 were included. Among practices participating in RISE, we assessed aggregated engagement with the QCDR dashboard and quality performance for 8 rheumatology-specific measures at the practice level. For each measure, the binomial generalized linear model was used to examine the association between dashboard engagement and measure performance, adjusting for EHR vendor, study year, and clustering at the practice level to account for repeated measures. Two types of engagement were analyzed: (1) measure-specific (interactions with patient-level information for a particular measure) and (2) global (interactions with any feature of the dashboard, classified into 4 profiles). Linear trends between the level of dashboard engagement and performance were also tested in the global analysis. In total, 211 practices were included in the study; over half were single-specialty practices. During their first year in the study, 65% of the practices had \"most\" or \"moderate\" levels of global engagement. In measure-specific analyses, we observed a positive but nonsignificant association of each individual and \"any\" actions with performance on 6-8 measures. However, having a ≥90th percentile number of drill-down views on 1 measure (rheumatoid arthritis (RA) periodic disease activity assessment) was statistically significant (odds ratio [OR] 2.3, 95% CI 1.2-4.3). In global analyses, we observed a similar pattern, where practices \"most\" engaged with the dashboard had higher odds of better performance compared to those with \"none.\" In total, 4 measures (osteoporosis screening, RA functional status assessment, RA periodic disease activity assessment, and gout serum urate target) had a statistically significant association with engagement and exhibited a \"dose-response\" relationship (P=.004, .02, <.001, and .04, respectively, for trend). Practices with \"any\" global engagement had higher performance on 6 out of 8 measures, again, with RA periodic disease activity assessment being statistically significant (OR 2.9, 95% CI 1.3-6.6). We found that higher levels of engagement were associated with higher performance on some, but not all, rheumatology-specific quality measures. Additional work is needed to understand whether the dashboard facilitates quality improvement or is merely a marker for high-performing practices.

The correspondence of cell state changes in diseased organs to peripheral protein signatures is currently unknown. Here, we generated and integrated single‐cell transcriptomic and proteomic data from multiple large pulmonary fibrosis patient cohorts. Integration of 233,638 single‐cell transcriptomes ( n  = 61) across three independent cohorts enabled us to derive shifts in cell type proportions and a robust core set of genes altered in lung fibrosis for 45 cell types. Mass spectrometry analysis of lung lavage fluid ( n  = 124) and plasma ( n  = 141) proteomes identified distinct protein signatures correlated with diagnosis, lung function, and injury status. A novel SSTR2+ pericyte state correlated with disease severity and was reflected in lavage fluid by increased levels of the complement regulatory factor CFHR1. We further discovered CRTAC1 as a biomarker of alveolar type‐2 epithelial cell health status in lavage fluid and plasma. Using cross‐modal analysis and machine learning, we identified the cellular source of biomarkers and demonstrated that information transfer between modalities correctly predicts disease status, suggesting feasibility of clinical cell state monitoring through longitudinal sampling of body fluid proteomes. Synopsis Multi‐modal integration of single‐cell RNA‐seq data from lung tissue and proteomic data from body fluids across independent lung fibrosis patient cohorts revealed biomarker signatures that correspond with cell state changes during disease progression. Changes in gene expression and cell type frequency are reproducible across cohorts. Protein biomarker signatures of lung function decline in pulmonary fibrosis. Multi‐modal data transfer identifies cellular source of regulated proteins. An activated pericyte state features inflammatory and complement regulators. CRTAC1 levels in body fluids indicate AT2 cell dedifferentiation in disease. Graphical Abstract Multi‐modal integration of single‐cell RNA‐seq data from lung tissue and proteomic data from body fluids across independent lung fibrosis patient cohorts revealed biomarker signatures that correspond with cell state changes during disease progression.

Background Screening colonoscopy (SC) outcome quality is best determined by the adenoma detection rate (ADR). The substantial variability in the ADRs between endoscopists may reflect different skills, experience and/or equipment. Objective To analyse the potential factors that may influence ADR variance, including case volume. Design 12 134 consecutive SCs (mean age 64.5 years, 47% men) from 21 Berlin private-practice colonoscopists were prospectively studied during 18 months. The data were analysed using a two-level mixed linear model to adequately address the characteristics of patients and colonoscopists. The ADR was regressed after considering the following factors: sex, age, bowel cleanliness, NSAID intake, annual SC case volume, lifetime experience, instrument withdrawal times, instrument generations used, and the number of annual continuing medical education (CME) meetings attended by the physician. The case volume was also retrospectively analysed from the 2007 national SC registry data (312 903 colonoscopies and 1004 colonoscopists). Results The patient factors that correlated with the ADR were sex, age (p<0.001) and low quality of bowel preparation (p=0.005). The factors that were related to the colonoscopists were the number of CME meetings attended (p=0.012) and instrument generation (p=0.001); these factors accounted for approximately 40% of the interphysician variability. Within a narrow range (6–11 min), the withdrawal time was not correlated with the ADR. Annual screening case volume did not correlate with the ADR, and this finding was confirmed by the German registry data. Conclusions The outcome quality of screening colonoscopies is mainly influenced by individual colonoscopist factors (ie, CME activities) and instrument quality. Clinical trial registration number Clinical Trial Gov Registration number: NCT00860665.