Optimising the use of colonoscopy to improve risk stratification for colorectal cancer in symptomatic patients: A decision-curve analysis.

OBJECTIVES: Pressured healthcare resources make risk stratification and patient prioritisation fundamental issues for the investigation of colorectal cancer (CRC) in symptomatic patients. The present study uses machine learning algorithms and decision strategies to improve the appropriate use of colonoscopy. DESIGN: All symptomatic patients in a single health board (2018-2021) proceeding to colonoscopy to investigate for CRC were included. Machine learning algorithms (NeuralNetwork, randomForest, Logistic regression, Naïve-Bayes and Adaboost) were used to risk-stratify patients for CRC using demographics, symptoms, quantitative faecal immunochemical test (qFIT) and haematological tests. Decision curve analyses were performed to determine the optimal decision strategies. RESULTS: 3776 patients were included (median age, 65; M:F,0.9:1.0) and CRC was identified in 217 patients (5.7%). qFIT > 400 µg Hb/g was the most important variable (%IncMSE = 78.5). RandomForrest had the highest area under curve (0.91) and accuracy (0.80) for CRC. When utilising decision curve analysis (DCA), 30%, 46% and 54% of colonoscopies were saved at accepted CRC probabilities of 1%, 2% and 3%, respectively. RandomForrest modelling had superior net clinical benefit compared to default colonoscopy strategies. CONCLUSIONS: MLA-derived decision strategies that account for patient and referrer risk preference reduce colonoscopy demand and carry net clinical benefit compared to default colonoscopy strategies.

Utility of new image-derived biomarkers for autosomal dominant polycystic kidney disease prognosis using automated instance cyst segmentation.

New image-derived biomarkers for patients affected by autosomal dominant polycystic kidney disease are needed to improve current clinical management. The measurement of total kidney volume (TKV) provides critical information for clinicians to drive care decisions. However, patients with similar TKV may present with very different phenotypes, often requiring subjective decisions based on other factors (e.g., appearance of healthy kidney parenchyma, a few cysts contributing significantly to overall TKV, etc.). In this study, we describe a new technique to individually segment cysts and quantify biometric parameters including cyst volume, cyst number, parenchyma volume, and cyst parenchyma surface area. Using data from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) study the utility of these new parameters was explored, both quantitatively as well as visually. Total cyst number and cyst parenchyma surface area showed superior prediction of the slope of estimated glomerular filtration rate decline, kidney failure and chronic kidney disease stages 3A, 3B, and 4, compared to TKV. In addition, presentations such as a few large cysts contributing significantly to overall kidney volume were shown to be much better stratified in terms of outcome predictions. Thus, these new image biomarkers, which can be obtained automatically, will have great utility in future studies and clinical care for patients affected by autosomal dominant polycystic kidney disease.

Specialized stellate cells offer a privileged route for rapid water flux in Drosophila renal tubule.

Insects are highly successful, in part through an excellent ability to osmoregulate. The renal (Malpighian) tubules can secrete fluid faster on a per-cell basis than any other epithelium, but the route for these remarkable water fluxes has not been established. In Drosophila melanogaster, we show that 4 genes of the major intrinsic protein family are expressed at a very high level in the fly renal tissue: the aquaporins (AQPs) Drip and Prip and the aquaglyceroporins Eglp2 and Eglp4 As predicted from their structure, and by their transport function by expressing these proteins in Xenopus oocytes, Drip, Prip, and Eglp2 show significant and specific water permeability, whereas Eglp2 and Eglp4 show very high permeability to glycerol and urea. Knockdowns of any of these genes result in impaired hormone-induced fluid secretion. The Drosophila tubule has 2 main secretory cell types: active cation-transporting principal cells, wherein the aquaglyceroporins localize to opposite plasma membranes, and small stellate cells, the site of the chloride shunt conductance, with these AQPs localizing to opposite plasma membranes. This suggests a model in which osmotically obliged water flows through the stellate cells. Consistent with this model, fluorescently labeled dextran, an in vivo marker of membrane water permeability, is trapped in the basal infoldings of the stellate cells after kinin diuretic peptide stimulation, confirming that these cells provide the major route for transepithelial water flux. The spatial segregation of these components of epithelial water transport may help to explain the unique success of the higher insects in regulating their internal environments.

Expression of the regulated isoform of the electrogenic Na+/HCO3- cotransporter, NBCe1, is enriched in pacemaker interstitial cells of Cajal.

Interstitial cells of Cajal (ICCs) generate electrical slow waves, which are required for normal gastrointestinal motility. The mechanisms for generation of normal pacemaking are not fully understood. Normal gastrointestinal contractility- and electrical slow-wave activity depend on the presence of extracellular HCO3-. Previous transcriptional analysis identified enrichment of mRNA encoding the electrogenic Na+/HCO3- cotransporter (NBCe1) gene (Slc4a4) in pacemaker myenteric ICCs in mouse small intestine. We aimed to determine the distribution of NBCe1 protein in ICCs of the mouse gastrointestinal tract and to identify the transcripts of the Slc4a4 gene in mouse and human small intestinal tunica muscularis. We determined the distribution of NBCe1 immunoreactivity (NBCe1-IR) by immunofluorescent labeling in mouse and human tissues. In mice, NBCe1-IR was restricted to Kit-positive myenteric ICCs of the stomach and small intestine and submuscular ICCs of the large intestine, that is, the slow wave generating subset of ICCs. Other subtypes of ICCs were NBCe1-negative. Quantitative real-time PCR identified >500-fold enrichment of Slc4a4-207 and Slc4a4-208 transcripts ["IP3-receptor-binding protein released by IP3" (IRBIT)-regulated isoforms] in Kit-expressing cells isolated from KitcreERT2/+, Rpl22tm1.1Psam/Sj mice and from single GFP-positive ICCs from Kittm1Rosay mice. Human jejunal tunica muscularis ICCs were also NBCe1-positive, and SLC4A4-201 and SLC4A4-204 RNAs were >300-fold enriched relative to SLC4A4-202. In summary, NBCe1 protein expressed in ICCs with electrical pacemaker function is encoded by Slc4a4 gene transcripts that generate IRBIT-regulated isoforms of NBCe1. In conclusion, Na+/HCO3- cotransport through NBCe1 contributes to the generation of pacemaker activity in subsets of ICCs.NEW & NOTEWORTHY In this study, we show that the electrogenic Na+/HCO3- cotransporter, NBCe1/Slc4a4, is expressed in subtypes of interstitial cells of Cajal (ICCs) responsible for electrical slow wave generation throughout the mouse gastrointestinal tract and is absent in other types of ICCs. The transcripts of Slc4a4 expressed in mouse ICCs and human gastrointestinal smooth muscle are the regulated isoforms. This indicates a key role for HCO3- transport in generation of gastrointestinal motility patterns.

Confronting Uncertainties of Simulated Air Pollution Concentrations during Persistent Cold Air Pool Events in the Salt Lake Valley, Utah.

Air pollutant accumulations during wintertime persistent cold air pool (PCAP) events in mountain valleys are of great concern for public health worldwide. Uncertainties associated with the simulated meteorology under stable conditions over complex terrain hinder realistic simulations of air quality using chemical transport models. We use the Community Multiscale Air Quality (CMAQ) model to simulate the gaseous and particulate species for 1 month in January 2011 during the Persistent Cold Air Pool Study (PCAPS) in the Salt Lake Valley (SLV), Utah (USA). Results indicate that the temporal variability associated with the elevated NOx and PM2.5 concentrations during PCAP events was captured by the model (r = 0.20 for NOx and r = 0.49 for PM2.5). However, concentrations were not at the correct magnitude (NMB = -35/12% for PM2.5 during PCAPs/non-PCAPs), where PM2.5 was underestimated during PCAP events and overestimated during non-PCAP periods. The underestimated PCAP strength is represented by valley heat deficit, which contributed to the underestimated PM2.5 concentrations compared with observations due to the model simulating more vertical mixing and less stable stratification than what was observed. Based on the observations, the dominant PM2.5 species were ammonium and nitrate. We provide a discussion that aims to investigate the emissions and chemistry model uncertainties using the nitrogen ratio method and the thermodynamic ammonium nitrate regime method.

Acute associations between heatwaves and preterm and early-term birth in 50 US metropolitan areas: a matched case-control study.

BACKGROUND: The effect of heatwaves on adverse birth outcomes is not well understood and may vary by how heatwaves are defined. The study aims to examine acute associations between various heatwave definitions and preterm and early-term birth. METHODS: Using national vital records from 50 metropolitan statistical areas (MSAs) between 1982 and 1988, singleton preterm (< 37 weeks) and early-term births (37-38 weeks) were matched (1:1) to controls who completed at least 37 weeks or 39 weeks of gestation, respectively. Matching variables were MSA, maternal race, and maternal education. Sixty heatwave definitions including binary indicators for exposure to sustained heat, number of high heat days, and measures of heat intensity (the average degrees over the threshold in the past 7 days) based on the 97.5th percentile of MSA-specific temperature metrics, or the 85th percentile of positive excessive heat factor (EHF) were created. Odds ratios (OR) for heatwave exposures in the week preceding birth (or corresponding gestational week for controls) were estimated using conditional logistic regression adjusting for maternal age, marital status, and seasonality. Effect modification by maternal education, age, race/ethnicity, child sex, and region was assessed. RESULTS: There were 615,329 preterm and 1,005,576 early-term case-control pairs in the analyses. For most definitions, exposure to heatwaves in the week before delivery was consistently associated with increased odds of early-term birth. Exposure to more high heat days and more degrees above the threshold yielded higher magnitude ORs. For exposure to 3 or more days over the 97.5th percentile of mean temperature in the past week compared to zero days, the OR was 1.027 for early-term birth (95%CI: 1.014, 1.039). Although we generally found null associations when assessing various heatwave definitions and preterm birth, ORs for both preterm and early-term birth were greater in magnitude among Hispanic and non-Hispanic black mothers. CONCLUSION: Although associations varied across metrics and heatwave definitions, heatwaves were more consistently associated with early-term birth than with preterm birth. This study's findings may have implications for prevention programs targeting vulnerable subgroups as climate change progresses.

Cloning, function, and localization of human, canine, and Drosophila ZIP10 (SLC39A10), a Zn2+ transporter.

Zinc (Zn2+) is the second most abundant trace element, but is considered a micronutrient, as it is a cofactor for many enzymes and transcription factors. Whereas Zn2+ deficiency can cause cognitive immune or metabolic dysfunction and infertility, excess Zn2+ is nephrotoxic. As for other ions and solutes, Zn2+ is moved into and out of cells by specific membrane transporters: ZnT, Zip, and NRAMP/DMT proteins. ZIP10 is reported to be localized at the apical membrane of renal proximal tubules in rats, where it is believed to play a role in Zn2+ import. Renal regulation of Zn2+ is of particular interest in light of growing evidence that Zn2+ may play a role in kidney stone formation. The objective of this study was to show that ZIP10 homologs transport Zn2+, as well as ZIP10, kidney localization across species. We cloned ZIP10 from dog, human, and Drosophila ( CG10006), tested clones for Zn2+ uptake in Xenopus oocytes and localized the protein in renal structures. CG10006, rather than foi (fear-of-intimacy, CG6817) is the primary ZIP10 homolog found in Drosophila Malpighian tubules. The ZIP10 antibody recognizes recombinant dog, human, and Drosophila ZIP10 proteins. Immunohistochemistry reveals that ZIP10 in higher mammals is found not only in the proximal tubule, but also in the collecting duct system. These ZIP10 proteins show Zn2+ transport. Together, these studies reveal ZIP10 kidney localization, a role in renal Zn2+ transport, and indicates that CG10006 is a Drosophila homolog of ZIP10.

A Bayesian ensemble approach to combine PM2.5 estimates from statistical models using satellite imagery and numerical model simulation.

Ambient fine particulate matter less than 2.5 µm in aerodynamic diameter (PM2.5) has been linked to various adverse health outcomes. PM2.5 arises from both natural and anthropogenic sources, and PM2.5 concentrations can vary over space and time. However, the sparsity of existing air quality monitors greatly restricts the spatial-temporal coverage of PM2.5 measurements, potentially limiting the accuracy of PM2.5-related health studies. Various methods exist to address these limitations by supplementing air quality monitoring measurements with additional data. We develop a method to combine PM2.5 estimated from satellite-retrieved aerosol optical depth (AOD) and chemical transport model (CTM) simulations using statistical models. While most previous methods utilize AOD or CTM separately, we aim to leverage advantages offered by both data sources in terms of resolution and coverage using Bayesian ensemble averaging. Our approach differs from previous ensemble approaches in its ability to not only incorporate uncertainties in PM2.5 estimates from individual models but also to provide uncertainties for the resulting ensemble estimates. In an application of estimating daily PM2.5 in the Southeastern US, the ensemble approach outperforms previously developed spatial-temporal statistical models that use either AOD or bias-corrected CTM simulations in cross-validation (CV) analyses. More specifically, in spatially clustered CV experiments, the ensemble approach reduced the AOD-only and CTM-only model's root mean squared error (RMSE) by at least 13%. Similar improvements were seen in R2. The enhanced prediction performance that the ensemble technique provides at fine-scale spatial resolution, as well as the availability of prediction uncertainty, can be further used in health effect analyses of air pollution exposure.

Comparison of Psychological and Physiological Responses to Imposed vs. Self-selected High-Intensity Interval Training.

Kellogg, E, Cantacessi, C, McNamer, O, Holmes, H, von Bargen, R, Ramirez, R, Gallagher, D, Vargas, S, Santia, B, Rodriguez, K, and Astorino, TA. Comparison of psychological and physiological responses to imposed vs. self-selected high-intensity interval training. J Strength Cond Res 33(11): 2945-2952, 2019-High-intensity interval training elicits similar physiological adaptations as moderate intensity continuous training (MICT). Some studies report greater enjoyment to a bout of high-intensity interval exercise (HIIE) vs. MICT, which is surprising considering that HIIE is more intense and typically imposed on the participant. This study compared physiological and perceptual responses between imposed and self-selected HIIE. Fourteen adults (age = 24 ± 3 years) unfamiliar with HIIE initially performed ramp exercise to exhaustion to measure maximal oxygen uptake (VO2max) followed by 2 subsequent sessions whose order was randomized. Imposed HIIE consisted of eight 60 seconds bouts at 80 percent peak power output (%PPO) separated by 60 seconds recovery at 10 %PPO. Self-selected HIIE (HIIESS) followed the same structure, but participants freely selected intensity in increments of 10 %PPO to achieve a rating of perceived exertion (RPE) ≥7. During exercise, heart rate, VO2, blood lactate concentration (BLa), affect (+5 to -5), and RPE were assessed. Physical Activity Enjoyment Scale was measured after exercise. Results showed higher VO2 (+10%, p = 0.013), BLa (p = 0.001), and RPE (p = 0.001) in HIIESS vs. HIIEIMP, and lower affect (p = 0.01), and enjoyment (87.6 ± 15.7 vs. 95.7 ± 11.7, p = 0.04). There was a significantly higher power output in self-selected vs. imposed HIIE (263.9 ± 81.4 W vs. 225.2 ± 59.6 W, p < 0.001). Data suggest that intensity mediates affective responses rather than the mode of HIIE performed by the participant.

Development of a Multispectral Albedometer and Deployment on an Unmanned Aircraft for Evaluating Satellite Retrieved Surface Reflectance over Nevada's Black Rock Desert.

Bright surfaces across the western U.S. lead to uncertainties in satellite derived aerosol optical depth (AOD) where AOD is typically overestimated. With this in mind, a compact and portable instrument was developed to measure surface albedo on an unmanned aircraft system (UAS). This spectral albedometer uses two Hamamatsu micro-spectrometers (range: 340⁻780 nm) for measuring incident and reflected solar radiation at the surface. The instrument was deployed on 5 October 2017 in Nevada's Black Rock Desert (BRD) to investigate a region of known high surface reflectance for comparison with albedo products from satellites. It was found that satellite retrievals underestimate surface reflectance compared to the UAS mounted albedometer. To highlight the importance of surface reflectance on the AOD from satellite retrieval algorithms, a 1-D radiative transfer model was used. The simple model was used to determine the sensitivity of AOD with respect to the change in albedo and indicates a large sensitivity of AOD retrievals to surface reflectance for certain combinations of surface albedo and aerosol optical properties. This demonstrates the need to increase the number of surface albedo measurements and an intensive evaluation of albedo satellite retrievals to improve satellite-derived AOD. The portable instrument is suitable for other applications as well.

Development of PM2.5 Source Profiles Using a Hybrid Chemical Transport-Receptor Modeling Approach.

Laboratory-based or in situ PM2.5 source profiles may not represent the pollutant composition for the sources in a different study location due to spatially and temporally varying characteristics, such as fuel or crustal element composition, or due to differences in emissions behavior under ambient versus laboratory conditions. In this work, PM2.5 source profiles were estimated for 20 sources using a novel optimization approach that incorporates observed concentrations with source impacts from a chemical transport model (CTM) to capture local pollutant characteristics. Nonlinear optimization was used to minimize the error between source profiles, CTM source impacts, and observations. In a 2006 U.S. application, spatial and seasonal variability was seen for coal combustion, dust, fires, metals processing, and other source profiles when compared to the reference profiles, with variability in species fractions over 400% (calcium in dust) compared to mean contributions of the same species. Revised profiles improved the spatial and temporal bias in modeled concentrations of several trace metal species, including Na, Al, Ca, Mn, Cu, As, Se, Br, and Pb. In an application of the CMB-iteration model for two U.S. cities, revised profiles estimated higher biomass burning and dust impacts for summer compared with previous studies. Source profile optimization can be useful for source apportionment studies that have limited availability of source profile data for the location of interest.

Evidence for Different Reactive Hg Sources and Chemical Compounds at Adjacent Valley and High Elevation Locations.

The spatial distribution of chemical compounds and concentration of reactive mercury (RM), defined as the sum of gaseous oxidized mercury (GOM) and <3 µm particulate bound mercury (PBM), are poorly characterized. The objective of this study was to understand the chemistry, concentration, and spatial and temporal distribution of GOM at adjacent locations (12 km apart) with a difference in elevation of ∼1000 m. Atmospheric GOM measurements were made with passive and active samplers using membranes, and at one location, a Tekran mercury measurement system was used. The chemistry of GOM varied across time and location. On the basis of data collected, chemistry at the low elevation site adjacent to a highway was primarily influenced by pollutants generated by mobile sources (GOM = nitrogen and sulfur-based compounds), and the high elevation site (GOM = halogen-based compounds) was affected by long-range transport in the free troposphere over the marine boundary layer into Nevada. Data collected at these two locations demonstrate that different GOM compounds exist depending on the oxidants present in the air. Measurements of GOM made by the KCl denuder in the Tekran instrument located at the low elevation site were lower than that measured using membranes by 1.7-13 times. Accurate measurements of atmospheric concentrations and chemistry of RM are necessary for proper assessment of environmental impacts, and field measurements are essential for atmospheric models, which in turn influence policy decisions.

Method for Fusing Observational Data and Chemical Transport Model Simulations To Estimate Spatiotemporally Resolved Ambient Air Pollution.

Investigations of ambient air pollution health effects rely on complete and accurate spatiotemporal air pollutant estimates. Three methods are developed for fusing ambient monitor measurements and 12 km resolution chemical transport model (CMAQ) simulations to estimate daily air pollutant concentrations across Georgia. Temporal variance is determined by observations in one method, with the annual mean CMAQ field providing spatial structure. A second method involves scaling daily CMAQ simulated fields using mean observations to reduce bias. Finally, a weighted average of these results based on prediction of temporal variance provides optimized daily estimates for each 12 × 12 km grid. These methods were applied to daily metrics of 12 pollutants (CO, NO2, NOx, O3, SO2, PM10, PM2.5, and five PM2.5 components) over the state of Georgia for a seven-year period (2002-2008). Cross-validation demonstrates a wide range in optimized model performance across pollutants, with SO2 predicted most poorly due to limitations in coal combustion plume monitoring and modeling. For the other pollutants studied, 54-88% of the spatiotemporal variance (Pearson R(2) from cross-validation) was captured, with ozone and PM2.5 predicted best. The optimized fusion approach developed provides daily spatial field estimates of air pollutant concentrations and uncertainties that are consistent with observations, emissions, and meteorology.

Turbulent Fluxes and Pollutant Mixing during Wintertime Air Pollution Episodes in Complex Terrain.

Cold air pools (CAPs) are stagnant stable air masses that form in valleys and basins in the winter. Low wintertime insolation limits convective mixing, such that pollutant concentrations can build up within the CAP when pollutant sources are present. In the western United States, wintertime CAPs often persist for days or weeks. Atmospheric models do not adequately capture the strength and evolution of CAPs. This is in part due to the limited availability of data quantifying the local turbulence during the formation, maintenance, and destruction of persistent CAPs. This paper presents observational data to quantify the turbulent mixing during two CAP episodes in Utah's Salt Lake Valley during February of 2004. Particulate matter (PM) concentration data and turbulence measurements for CAP and non-CAP time periods indicate that two distinct types of mixing scenarios occur depending on whether the CAP is dry or cloudy. Where cloudy, CAPs have enhanced vertical mixing due to top-down convection from the cloud layer. A comparison between the heat and momentum fluxes during 5 days of a dry CAP episode in February to those of an equivalent 5 day time period in March with no CAP indicates that the average turbulent kinetic energy during the CAP was suppressed by approximately 80%.

Investigation of time-resolved atmospheric conditions and indoor/outdoor particulate matter concentrations in homes with gas and biomass cook stoves in Nogales, Sonora, Mexico.

This paper reports findings from a case study designed to investigate indoor and outdoor air quality in homes near the United States-Mexico border During the field study, size-resolved continuous particulate matter (PM) concentrations were measured in six homes, while outdoor PM was simultaneously monitored at the same location in Nogales, Sonora, Mexico, during March 14-30, 2009. The purpose of the experiment was to compare PM in homes using different fuels for cooking, gas versus biomass, and to obtain a spatial distribution of outdoor PM in a region where local sources vary significantly (e.g., highway, border crossing, unpaved roads, industry). Continuous PM data were collected every 6 seconds using a valve switching system to sample indoor and outdoor air at each home location. This paper presents the indoor PM data from each home, including the relationship between indoor and outdoor PM. The meteorological conditions associated with elevated ambient PM events in the region are also discussed. Results indicate that indoor air pollution has a strong dependence on cooking fuel, with gas stoves having hourly averaged median PM3 concentrations in the range of 134 to 157 microg m(-3) and biomass stoves 163 to 504 microg m(-1). Outdoor PM also indicates a large spatial heterogeneity due to the presence of microscale sources and meteorological influences (median PM3: 130 to 770 microg m(-3)). The former is evident in the median and range of daytime PM values (median PM3: 250 microg m(-3), maximum: 9411 microg m(-3)), while the meteorological influences appear to be dominant during nighttime periods (median PM3: 251 microg m(-3), maximum: 10,846 microg m(-3)). The atmospheric stability is quantified for three nighttime temperature inversion episodes, which were associated with an order of magnitude increase in PM10 at the regulatory monitor in Nogales, AZ (maximum increase: 12 to 474 microg m(-3)). Implications: Regulatory air quality standards are based on outdoor ambient air measurements. However, a large fraction of time is typically spent indoors where a variety of activities including cooking, heating, tobacco smoking, and cleaning can lead to elevated PM concentrations. This study investigates the influence of meteorology, outdoor PM, and indoor activities on indoor air pollution (IAP) levels in the United States-Mexico border region. Results indicate that cooking fuel type and meteorology greatly influence the IAP in homes, with biomass fuel use causing the largest increase in PM concentration.

Preterm and Early-Term Delivery After Heat Waves in 50 US Metropolitan Areas.

Importance: Heat waves are increasing in frequency, intensity, and duration and may be acutely associated with pregnancy outcomes. Objective: To examine changes in daily rates of preterm and early-term birth after heat waves in a 25-year nationwide study. Design, Setting, and Participants: This cohort study of singleton births used birth records from 1993 to 2017 from the 50 most populous US metropolitan statistical areas (MSAs). The study included 53 million births, covering 52.8% of US births over the period. Data were analyzed between October 2022 and March 2023 at the National Center for Health Statistics. Exposures: Daily temperature data from Daymet at 1-km2 resolution were averaged over each MSA using population weighting. Heat waves were defined in the 4 days (lag, 0-3 days) or 7 days (lag, 0-6 days) preceding birth. Main Outcomes and Measures: Daily counts of preterm birth (28 to <37 weeks), early-term birth (37 to <39 weeks), and ongoing pregnancies in each gestational week on each day were enumerated in each MSA. Rate ratios for heat wave metrics were obtained from time-series models restricted to the warm season (May to September) adjusting for MSA, year, day of season, and day of week, and offset by pregnancies at risk. Results: There were 53 154 816 eligible births in the 50 MSAs from 1993 to 2017; 2 153 609 preterm births and 5 795 313 early-term births occurring in the warm season were analyzed. A total of 30.0% of mothers were younger than 25 years, 53.8% were 25 to 34 years, and 16.3% were 35 years or older. Heat waves were positively associated with daily rates of preterm and early-term births, showing a dose-response association with heat wave duration and temperatures and stronger associations in the more acute 4-day window. After 4 consecutive days of mean temperatures exceeding the local 97.5th percentile, the rate ratio for preterm birth was 1.02 (95% CI, 1.00-1.03), and the rate ratio for early-term birth was 1.01 (95% CI, 1.01-1.02). For the same exposure, among those who were 29 years of age or younger, had a high school education or less, and belonged to a racial or ethnic minority group, the rate ratios were 1.04 (95% CI, 1.02-1.06) for preterm birth and 1.03 (95% CI, 1.02-1.05) for early-term birth. Results were robust to alternative heat wave definitions, excluding medically induced deliveries, and alternative statistical model specifications. Conclusions and Relevance: In this cohort study, preterm and early-term birth rates increased after heat waves, particularly among socioeconomically disadvantaged subgroups. Extreme heat events have implications for perinatal health.

Glycogen synthase kinase 3 activity enhances liver inflammation in MASH.

Background & Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is characterized by excessive circulating toxic lipids, hepatic steatosis, and liver inflammation. Monocyte adhesion to liver sinusoidal endothelial cells (LSECs) and transendothelial migration (TEM) are crucial in the inflammatory process. Under lipotoxic stress, LSECs develop a proinflammatory phenotype known as endotheliopathy. However, mediators of endotheliopathy remain unclear. Methods: Primary mouse LSECs isolated from C57BL/6J mice fed chow or MASH-inducing diets rich in fat, fructose, and cholesterol (FFC) were subjected to multi-omics profiling. Mice with established MASH resulting from a choline-deficient high-fat diet (CDHFD) or FFC diet were also treated with two structurally distinct GSK3 inhibitors (LY2090314 and elraglusib [9-ING-41]). Results: Integrated pathway analysis of the mouse LSEC proteome and transcriptome indicated that leukocyte TEM and focal adhesion were the major pathways altered in MASH. Kinome profiling of the LSEC phosphoproteome identified glycogen synthase kinase (GSK)-3ß as the major kinase hub in MASH. GSK3ß-activating phosphorylation was increased in primary human LSECs treated with the toxic lipid palmitate and in human MASH. Palmitate upregulated the expression of C-X-C motif chemokine ligand 2, intracellular adhesion molecule 1, and phosphorylated focal adhesion kinase, via a GSK3-dependent mechanism. Congruently, the adhesive and transendothelial migratory capacities of primary human neutrophils and THP-1 monocytes through the LSEC monolayer under lipotoxic stress were reduced by GSK3 inhibition. Treatment with the GSK3 inhibitors LY2090314 and elraglusib ameliorated liver inflammation, injury, and fibrosis in FFC- and CDHFD-fed mice, respectively. Immunophenotyping using cytometry by mass cytometry by time of flight of intrahepatic leukocytes from CDHFD-fed mice treated with elraglusib showed reduced infiltration of proinflammatory monocyte-derived macrophages and monocyte-derived dendritic cells. Conclusion: GSK3 inhibition attenuates lipotoxicity-induced LSEC endotheliopathy and could serve as a potential therapeutic strategy for treating human MASH. Impact and Implications: LSECs under lipotoxic stress in MASH develop a proinflammatory phenotype known as endotheliopathy, with obscure mediators and functional outcomes. The current study identified GSK3 as the major driver of LSEC endotheliopathy, examined its pathogenic role in myeloid cell-associated liver inflammation, and defined the therapeutic efficacy of pharmacological GSK3 inhibitors in murine MASH. This study provides preclinical data for the future investigation of GSK3 pharmacological inhibitors in human MASH. The results of this study are important to hepatologists, vascular biologists, and investigators studying the mechanisms of inflammatory liver disease and MASH, as well as those interested in drug development.

Robotic Ultrasound and Novel Collagen Analyses for Polycystic Kidney Disease Research Using Mice.

BACKGROUND: 3D imaging and histology are critical tools for assessing polycystic kidney disease ( PKD ) in patients and animal models. Magnetic resonance ( MR ) imaging provides micron resolution, but is time consuming, expensive, and access to equipment and expertise is limiting. Robotic ultrasound ( US ) imaging has lower spatial resolution but is faster, more cost effective, and accessible. Similarly, Picrosirius red ( PSR ) staining and brightfield microscopy is commonly used to assess fibrosis; however, alternative methods have been shown in non-kidney tissues to provide greater sensitivity and more detailed structural characterization. METHODS: In this study, we evaluated the utility of robotic US and alternative methods of quantifying PSR staining for PKD research. We compared longitudinal total kidney volume ( TKV ) measurements using US and MR. We additionally compared PSR imaging and quantification using standard brightfield with that by circularly polarized light with hue analysis, and fluorescence imaging analyzed using CT-FIRE software for automatic detection of individual collagen fibers. RESULTS: Increased TKV was detected by US in Pkd1RC/RC vs wild type ( WT ) at timepoints spanning early to established disease. US inter-observer variability was greater but allowed scanning in 2-5 minutes/mouse while MR required 20-30 minutes/mouse. While no change in fibrotic index was detected in this cohort of relatively mild disease using brightfield, polarized light showed fibers skewed thinner in Pkd1RC/RC vs WT. Fluorescence imaging showed a higher density of collagen fibers in Pkd1RC/RC vs WT, and fibers were thinner and curvier with no change in length. Additionally, fiber density was higher in both glomeruli and tubules in Pkd1RC/RC , and glomeruli had a higher fiber density than tubules in Pkd1RC/RC , and trended higher in WT. CONCLUSIONS: These studies show robotic ultrasound is a rigorous imaging tool for pre-clinical PKD research. Additionally, they demonstrate the increased sensitivity of polarized and fluorescence analysis of PSR-stained collagen.

Bayesian-based ensemble source apportionment of PM2.5.

A Bayesian source apportionment (SA) method is developed to provide source impact estimates and associated uncertainties. Bayesian-based ensemble averaging of multiple models provides new source profiles for use in a chemical mass balance (CMB) SA of fine particulate matter (PM2.5). The approach estimates source impacts and their uncertainties by using a short-term application of four individual SA methods: three receptor-based models and one chemical transport model. The method is used to estimate two seasonal distributions of source profiles that are used in SA for a long-term PM2.5 data set. For each day in a long-term PM2.5 data set, 10 source profiles are sampled from these distributions and used in a CMB application, resulting in 10 SA results for each day. This formulation results in a distribution of daily source impacts rather than a single value. The average and standard deviation of the distribution are used as the final estimate of source impact and a measure of uncertainty, respectively. The Bayesian-based source impacts for biomass burning correlate better with observed levoglucosan (R(2) = 0.66) and water-soluble potassium (R(2) = 0.63) than source impacts estimated using more traditional methods and more closely agrees with observed total mass. The Bayesian approach also captures the expected seasonal variation of biomass burning and secondary impacts and results in fewer days with sources having zero impact. Sensitivity analysis found that using non-informative prior weighting performed better than using weighting based on method-derived uncertainties. This approach can be applied to long-term data sets from speciation network sites of the United States Environmental Protection Agency (U.S. EPA). In addition to providing results that are more consistent with independent observations and known emission sources being present, the distributions of source impacts can be used in epidemiologic analyses to estimate uncertainties associated with the SA results.