Anaplastic lymphoma kinase-positive pulmonary inflammatory myofibroblastic tumour: a case report.

BACKGROUND: Pulmonary inflammatory myofibroblastic tumour (IMT) is a rare condition that usually presents in young individuals and is associated with anaplastic lymphoma kinase (ALK)-translocation. CASE PRESENTATION: We report a case of an 18-year-old Caucasian man with ALK-translocated pulmonary IMT treated with multimodality therapy. The patient presented with breathlessness and was found to have a collapsed left lung. Further investigations revealed an ALK-translocated pulmonary IMT. This is usually treated with an ALK-inhibitor but patient declined after discussing potential side-effects and had repeated rigid bronchoscopic interventions for local disease control. Due to persistent local recurrence, patient received radical external beam radiotherapy (EBRT) with pulse steroids, and one year later started on Ibuprofen, a non-steroidal anti-inflammatory agent (NSAID). Following multimodality treatment, he developed a complete response. He remains treatment-free for the past seven years. Eleven years on from his diagnosis, he remains in remission with a ECOG performance status of zero. CONCLUSIONS: Achieving long-term local control in pulmonary IMT can be challenging. Multimodality treatment is sometimes needed but the overall outlook remains good.

Health-Damaging Climate Events Highlight the Need for Interdisciplinary, Engaged Research.

In 2023 human populations experienced multiple record-breaking climate events, with widespread impacts on human health and well-being. These events include extreme heat domes, drought, severe storms, flooding, and wildfires. Due to inherent lags in the climate system, we can expect such extremes to continue for multiple decades after reaching net zero carbon emissions. Unfortunately, despite these significant current and future impacts, funding for research in climate and health has lagged behind that for other geoscience and biomedical research. While some initial efforts from funding agencies are evident, there is still a significant need to increase the resources available for multidisciplinary research in the face of this issue. As a group of experts at this important intersection, we call for a more concerted effort to encourage interdisciplinary and policy-relevant investigations into the detrimental health effects of continued climate change.

Adverse Health Impacts of Outdoor Air Pollution, Including from Wildland Fires, in the United States: "Health of the Air," 2018-2020.

Rationale: Adverse health impacts from outdoor air pollution occur across the United States, but the magnitude of these impacts varies widely by geographic region. Ambient pollutant concentrations, emission sources, baseline health conditions, and population sizes and distributions are all important factors that need to be taken into account to quantify local health burdens. Objectives: To determine health impacts from ambient air pollution concentrations in the United States that exceed the levels recommended by the American Thoracic Society. Methods: Using a methodology that has been well established in previous "Health of the Air" reports, this study provides policy-relevant estimates for every monitored county and city in the United States for the adverse health impacts of outdoor pollution concentrations using U.S. Environmental Protection Agency design values for years 2018-2020. Additionally, for the first time, the report includes adverse birth outcomes as well as estimates of health impacts specifically attributable to wildland fires using an exposure dataset generated through Community Multiscale Air Quality simulations. Results: The adverse health burdens attributable to air pollution occur across the entire age spectrum, including adverse birth outcomes (10,660 preterm and/or low-weight births; 95% confidence interval [CI], 3,180-18,330), in addition to mortality impacts (21,300 avoidable deaths; 95% CI, 16,180-26,200), lung cancer incidence (3,000 new cases; 95% CI, 1,550-4,390), multiple types of cardiovascular and respiratory morbidity (748,660 events; 95% CI, 326,050-1,057,080), and adversely impacted days (52.4 million days; 95% CI, 7.9-92.4 million days). Two different estimates of mortality impacts from wildland fires were created based on assumptions regarding the underlying toxicity of particles from wildland fires (low estimate of 4,080 deaths, 95% CI, 240-7,890; middle estimate of 28,000 deaths, 95% CI, 27,300-28,700). Conclusions: This year's report identified sizable health benefits that would be expected to occur across the United States with compliance with more health-protective air quality standards such as those recommended by the American Thoracic Society. This study also indicates that a large number of excess deaths are attributable to emissions from wildland fires; air quality management strategies outside what is required by the Clean Air Act will be needed to best address this important source of air pollution and its associated health risks.

Parentage influence on gene expression under acidification revealed through single-embryo sequencing.

The dissolution of anthropogenic carbon dioxide (CO2 ) in seawater has altered its carbonate chemistry in the process of ocean acidification (OA). OA affects the viability of marine species. In particular, calcifying organisms and their early planktonic larval stages are considered vulnerable. These organisms often utilize energy reserves for metabolism rather than growth and calcification as supported by bulk RNA-sequencing (RNA-seq) experiments. Yet, transcriptomic profiling of a bulk sample reflects the average gene expression of the population, neglecting the variations between individuals, which forms the basis for natural selection. Here, we used single-embryo RNA-seq on larval sea urchin Heliocidaris crassispina, which is a commercially and ecologically valuable species in East Asia, to document gene expression changes to OA at an individual and family level. Three paternal half-sibs groups were fertilized and exposed to 3 pH conditions (ambient pH 8.0, 7.7 and 7.4) for 12 h prior to sequencing and oxygen consumption assay. The resulting transcriptomic profile of all embryos can be distinguished into four clusters, with differences in gene expressions that govern biomineralization, cell differentiation and patterning, as well as metabolism. While these responses were influenced by pH conditions, the male identities also had an effect. Specifically, a regression model and goodness of fit tests indicated a significant interaction between sire and pH on the probability of embryo membership in different clusters of gene expression. The single-embryo RNA-seq approach is promising in climate stressor research because not only does it highlight potential impacts before phenotypic changes were observed, but it also highlights variations between individuals and lineages, thus enabling a better determination of evolutionary potential.

Impacts of the COVID-19 economic slowdown on soybean crop yields in the United States.

It is without question that the COVID-19 pandemic has taken its toll on the U.S. economy. Stay-at-home orders led to reduced vehicular traffic and widespread declines in anthropogenic emissions (e.g., nitrogen oxides (NOx)). This study is the first to explore the potential consequences of O3 changes resulting from the economic shutdown in the United States on soybean crop yields for 2020. The pandemic's impact on surface O3 is quantified using the NOAA's National Air Quality Forecasting Capability (NAQFC), which is based on the Community Multi-Scale Air Quality (CMAQ) model for May-July 2020. The "would-be", 2020 level business-as-usual (BAU) emissions are compared to a simulation that uses representative COVID-19 (C19) emissions. For each emissions scenario, crop exposures are calculated using the AOT40 cumulative exposure index and then combined with county-level soybean production totals to determine regional yield losses. Exposure changes ranged between - 2 and 2 ppmVhr-1. It was further shown that increased exposures (0.5 to 1.10 ppmVhr-1) in the Southeast U.S. counteracted decreased exposures (0.8 to 0.5 ppmVhr-1) in the other soybean-producing regions. As a result, corresponding yield improvements counteracted yield losses around the Mississippi River Valley and allowed for minimal improvements in soybean production loss totaling $6.5 million over CONUS.

Satellites reveal Earth's seasonally shifting dust emission sources.

Establishing mineral dust impacts on Earth's systems requires numerical models of the dust cycle. Differences between dust optical depth (DOD) measurements and modelling the cycle of dust emission, atmospheric transport, and deposition of dust indicate large model uncertainty due partially to unrealistic model assumptions about dust emission frequency. Calibrating dust cycle models to DOD measurements typically in North Africa, are routinely used to reduce dust model magnitude. This calibration forces modelled dust emissions to match atmospheric DOD but may hide the correct magnitude and frequency of dust emission events at source, compensating biases in other modelled processes of the dust cycle. Therefore, it is essential to improve physically based dust emission modules. Here we use a global collation of satellite observations from previous studies of dust emission point source (DPS) dichotomous frequency data. We show that these DPS data have little-to-no relation with MODIS DOD frequency. We calibrate the albedo-based dust emission model using the frequency distribution of those DPS data. The global dust emission uncertainty constrained by DPS data (±3.8 kg m-2 y-1) provides a benchmark for dust emission model development. Our calibrated model results reveal much less global dust emission (29.1 ± 14.9 Tg y-1) than previous estimates, and show seasonally shifting dust emission predominance within and between hemispheres, as opposed to a persistent North African dust emission primacy widely interpreted from DOD measurements. Earth's largest dust emissions, proceed seasonally from East Asian deserts in boreal spring, to Middle Eastern and North African deserts in boreal summer and then Australian shrublands in boreal autumn-winter. This new analysis of dust emissions, from global sources of varying geochemical properties, have far-reaching implications for current and future dust-climate effects. For more reliable coupled representation of dust-climate projections, our findings suggest the need to re-evaluate dust cycle modelling and benefit from the albedo-based parameterisation.

Self-assembled three-dimensional hydrogels based on graphene derivatives and cerium oxide nanoparticles: scaffolds for co-culture of oligodendrocytes and neurons derived from neural stem cells.

Stem cell-based therapies have shown promising results for the regeneration of the nervous system. However, the survival and integration of the stem cells in the neural circuitry is suboptimal and might compromise the therapeutic outcomes of this approach. The development of functional scaffolds capable of actively interacting with stem cells may overcome the current limitations of stem cell-based therapies. In this study, three-dimensional hydrogels based on graphene derivatives and cerium oxide (CeO2) nanoparticles are presented as prospective supports allowing neural stem cell adhesion, migration and differentiation. The morphological, mechanical and electrical properties of the resulting hydrogels can be finely tuned by controlling several parameters of the self-assembly of graphene oxide sheets, namely the amount of incorporated reducing agent (ascorbic acid) and CeO2 nanoparticles. The intrinsic properties of the hydrogels, as well as the presence of CeO2 nanoparticles, clearly influence the cell fate. Thus, stiffer adhesion substrates promote differentiation to glial cell lineages, while softer substrates enhance mature neuronal differentiation. Remarkably, CeO2 nanoparticle-containing hydrogels support the differentiation of neural stem cells to neuronal, astroglial and oligodendroglial lineage cells, promoting the in vitro generation of nerve tissue grafts that might be employed in neuroregenerative cell therapies.

Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States.

We present an unprecedented effort to map anthropogenic emissions of air pollutants at 1 km spatial resolution in the contiguous United States (CONUS). This new dataset, Neighborhood Emission Mapping Operation (NEMO), is produced at hourly intervals based on the United States Environmental Protection Agency (US EPA) National Emission Inventories 2017. Fine-scale spatial allocation was achieved through distributing the emission sources using 108 spatial surrogates, factors representing the portion of a source in each 1 km grid. Gaseous and particulate pollutants are speciated into model species for the Carbon Bond 6 chemical mechanism. All sources are grouped in 9 sectors and stored in NetCDF format for air quality models, and in shapefile format for GIS users and air quality managers. This dataset shows good consistency with the USEPA benchmark dataset, with a monthly difference in emissions less than 0.03% for any sector. NEMO provides the first 1 km mapping of air pollution over the CONUS, enabling new applications such as fine-scale air quality modeling, air pollution exposure assessment, and environmental justice studies.

A radiomics-based decision support tool improves lung cancer diagnosis in combination with the Herder score in large lung nodules.

BACKGROUND: Large lung nodules (≥15 mm) have the highest risk of malignancy, and may exhibit important differences in phenotypic or clinical characteristics to their smaller counterparts. Existing risk models do not stratify large nodules well. We aimed to develop and validate an integrated segmentation and classification pipeline, incorporating deep-learning and traditional radiomics, to classify large lung nodules according to cancer risk. METHODS: 502 patients from five U.K. centres were recruited to the large-nodule arm of the retrospective LIBRA study between July 2020 and April 2022. 838 CT scans were used for model development, split into training and test sets (70% and 30% respectively). An nnUNet model was trained to automate lung nodule segmentation. A radiomics signature was developed to classify nodules according to malignancy risk. Performance of the radiomics model, termed the large-nodule radiomics predictive vector (LN-RPV), was compared to three radiologists and the Brock and Herder scores. FINDINGS: 499 patients had technically evaluable scans (mean age 69 ± 11, 257 men, 242 women). In the test set of 252 scans, the nnUNet achieved a DICE score of 0.86, and the LN-RPV achieved an AUC of 0.83 (95% CI 0.77-0.88) for malignancy classification. Performance was higher than the median radiologist (AUC 0.75 [95% CI 0.70-0.81], DeLong p = 0.03). LN-RPV was robust to auto-segmentation (ICC 0.94). For baseline solid nodules in the test set (117 patients), LN-RPV had an AUC of 0.87 (95% CI 0.80-0.93) compared to 0.67 (95% CI 0.55-0.76, DeLong p = 0.002) for the Brock score and 0.83 (95% CI 0.75-0.90, DeLong p = 0.4) for the Herder score. In the international external test set (n = 151), LN-RPV maintained an AUC of 0.75 (95% CI 0.63-0.85). 18 out of 22 (82%) malignant nodules in the Herder 10-70% category in the test set were identified as high risk by the decision-support tool, and may have been referred for earlier intervention. INTERPRETATION: The model accurately segments and classifies large lung nodules, and may improve upon existing clinical models. FUNDING: This project represents independent research funded by: 1) Royal Marsden Partners Cancer Alliance, 2) the Royal Marsden Cancer Charity, 3) the National Institute for Health Research (NIHR) Biomedical Research Centre at the Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, 4) the National Institute for Health Research (NIHR) Biomedical Research Centre at Imperial College London, 5) Cancer Research UK (C309/A31316).

Efficacy and safety of one anastomosis gastric bypass versus Roux-en-Y gastric bypass for type 2 diabetes remission (ORDER): protocol of a multicentre, randomised controlled, open-label, superiority trial.

INTRODUCTION: Previous studies have demonstrated that one anastomosis gastric bypass (OAGB) is not inferior to Roux-en-Y gastric bypass (RYGB) in treating obesity. However, high level evidence comparing the efficacy and safety of both procedures in type 2 diabetes (T2D) treatment is still lacking, which is another main aim of bariatric surgery. The presented trial has been designed to aim at investigating the superiority of OAGB over the reference procedure RYGB in treating T2D as primary endpoint. And diabetes-related microvascular and macrovascular complications, cardiovascular comorbidities, weight loss, postoperative nutritional status, quality of life and overall complications will be followed up for 5 years as secondary endpoints. METHODS AND ANALYSIS: This prospective, multicentre, randomised superiority open-label trial will be conducted in patients of Asian descent. A total of 248 patients (BMI≥27.5 kg/m2) who are diagnosed with T2D will be randomly assigned (1:1) to OAGB or RYGB with blocks of four. The primary endpoint is the complete diabetes remission rate defined as HbA1c≤6.0% and fasting plasma glucose≤5.6 mmol/L without any antidiabetic medications at 1 year after surgery. All secondary endpoints will be measured at different follow-up visit points, which will start at least 3 months after enrolment, with a continuous annual follow-up for five postoperative years in order to provide solid evidence on the efficacy and safety of OAGB in patients with T2D. ETHICS AND DISSEMINATION: The study has been approved by the ethics committee of leading centre (Beijing Friendship Hospital, Capital Medical University, no. 2021-P2-037-03). The results generated from this work will be disseminated to academic audiences and the public via publications in international peer-reviewed journals and conferences. The data presented will be imported into a national data registry. Findings are expected to be available in 2025, which will facilitate clinical decision-making in the field. TRIAL REGISTRATION NUMBER: NCT05015283.

Dust Storms, Valley Fever, and Public Awareness.

We discuss several issues raised by Comrie (2021, https://doi.org/10.1029/2021GH000504), which uses a crowdsourced data set to study dust storms and coccidioidomycosis (Valley fever). There is inconsistency in the term "dust storm" used by science communities. The dust data from National Oceanic and Atmospheric Administration Storm Events Database are from diverse sources, unsuitable for assessing dust-coccidioidomycosis relationships. Population exposure to dust or Coccidioides needs to consider the frequency, magnitude, and duration of dust events. Given abundant evidence that dust storms are a viable driver to transport pathogens, it is in best public interest to advocate dust storms may put people at risk for contracting Valley fever.

Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16.

A new dynamical core, known as the Finite-Volume Cubed-Sphere (FV3) and developed at both NASA and NOAA, is used in NOAA's Global Forecast System (GFS) and in limited-area models for regional weather and air quality applications. NOAA has also upgraded the operational FV3GFS to version 16 (GFSv16), which includes a number of significant developmental advances to the model configuration, data assimilation, and underlying model physics, particularly for atmospheric composition to weather feedback. Concurrent with the GFSv16 upgrade, we couple the GFSv16 with the Community Multiscale Air Quality (CMAQ) model to form an advanced version of the National Air Quality Forecasting Capability (NAQFC) that will continue to protect human and ecosystem health in the US. Here we describe the development of the FV3GFSv16 coupling with a "state-of-the-science" CMAQ model version 5.3.1. The GFS-CMAQ coupling is made possible by the seminal version of the NOAA-EPA Atmosphere-Chemistry Coupler (NACC), which became a major piece of the next operational NAQFC system (i.e., NACC-CMAQ) on 20 July 2021. NACC-CMAQ has a number of scientific advancements that include satellite-based data acquisition technology to improve land cover and soil characteristics and inline wildfire smoke and dust predictions that are vital to predictions of fine particulate matter (PM2.5) concentrations during hazardous events affecting society, ecosystems, and human health. The GFS-driven NACC-CMAQ model has significantly different meteorological and chemical predictions compared to the previous operational NAQFC, where evaluation of NACC-CMAQ shows generally improved near-surface ozone and PM2.5 predictions and diurnal patterns, both of which are extended to a 72 h (3 d) forecast with this system.

Fabrication and nanoscale properties of PEDOT:PSS conducting polymer nanospheres.

Electrically conducting nanospheres of poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) with tailored size were prepared using a solvent displacement technique. To fabricate these nanostructures, dried PEDOT:PSS was dissolved in ethylene glycol (EG) and the solution was precipitated in deionized water. The proposed fabrication route allowed obtaining a water-based dispersion of PEDOT:PSS nanospheres with good optical properties. To determine the physical properties of the nanospheres, we followed a nanoscale approach, using atomic force microscopy. Our nanoscale mechanical and electrical investigations showed that the nanospheres retained good physical and conductivity properties, compared to the commercial product. Moreover, the local studies indicated that the reprecipitation process and the spherical shape lead to a different arrangement of the PSS and PEDOT phases.

Pronounced increases in nitrogen emissions and deposition due to the historic 2020 wildfires in the western U.S.

Wildfire outbreaks can lead to extreme biomass burning (BB) emissions of both oxidized (e.g., nitrogen oxides; NOx = NO+NO2) and reduced form (e.g., ammonia; NH3) nitrogen (N) compounds. High N emissions are major concerns for air quality, atmospheric deposition, and consequential human and ecosystem health impacts. In this study, we use both satellite-based observations and modeling results to quantify the contribution of BB to the total emissions, and approximate the impact on total N deposition in the western U.S. Our results show that during the 2020 wildfire season of August-October, BB contributes significantly to the total emissions, with a satellite-derived fraction of NH3 to the total reactive N emissions (median ~ 40%) in the range of aircraft observations. During the peak of the western August Complex Fires in September, BB contributed to ~55% (for the contiguous U.S.) and ~ 83% (for the western U.S.) of the monthly total NOx and NH3 emissions. Overall, there is good model performance of the George Mason University-Wildfire Forecasting System (GMU-WFS) used in this work. The extreme BB emissions lead to significant contributions to the total N deposition for different ecosystems in California, with an average August - October 2020 relative increase of ~78% (from 7.1 to 12.6 kg ha-1 year-1) in deposition rate to major vegetation types (mixed forests + grasslands/shrublands/savanna) compared to the GMU-WFS simulations without BB emissions. For mixed forest types only, the average N deposition rate increases (from 6.2 to 16.9 kg ha-1 year-1) are even larger at ~173%. Such large N deposition due to extreme BB emissions are much (~6-12 times) larger than low-end critical load thresholds for major vegetation types (e.g., forests at 1.5-3 kg ha-1 year-1), and thus may result in adverse N deposition effects across larger areas of lichen communities found in California's mixed conifer forests.

Does the modified Glasgow Prognostic Score aid in the management of patients undergoing surgery for a soft-tissue sarcoma? : an international multicentre study.

AIMS: The modified Glasgow Prognostic Score (mGPS) uses preoperative CRP and albumin to calculate a score from 0 to 2 (2 being associated with poor outcomes). mGPS is validated in multiple carcinomas. To date, its use in soft-tissue sarcoma (STS) is limited, with only small cohorts reporting that increased mGPS scores correlates with decreased survival in STS patients. METHODS: This retrospective multicentre cohort study identified 493 STS patients using clinical databases from six collaborating hospitals in three countries. Centres performed a retrospective data collection for patient demographics, preoperative blood results (CRP and albumin levels and neutrophil, leucocyte, and platelets counts), and oncological outcomes (disease-free survival, local, or metastatic recurrence) with a minimum of two years' follow-up. RESULTS: We found that increased mGPS, tumour size, grade, neutrophil/lymphocyte ratio, and disease recurrence were associated with reduced survival. Importantly, mGPS was the best at stratifying prognosis and could be used in conjunction with tumour grade to sub-stratify patient survival. CONCLUSION: This study demonstrated that prognosis of localized STS strongly correlates with mGPS, as an increasing score is associated with a poorer outcome. We note that 203 patients (41%) with an STS have evidence of systemic inflammation. We recommend the mGPS and other biochemical blood indicators be introduced into the routine diagnostic assessment in STS patients to stratify patient prognosis. Its use will support clinical decision-making, especially when morbid treatment options such as amputation are being considered. Cite this article: Bone Joint J 2022;104-B(1):168-176.

Impacts of the COVID-19 economic slowdown on ozone pollution in the U.S.

In this work, we use observations and experimental emissions in a version of NOAA's National Air Quality Forecasting Capability to show that the COVID-19 economic slowdown led to disproportionate impacts on near-surface ozone concentrations across the contiguous U.S. (CONUS). The data-fusion methodology used here includes both U.S. EPA Air Quality System ground and the NASA Aura satellite Ozone Monitoring Instrument (OMI) NO2 observations to infer the representative emissions changes due to the COVID-19 economic slowdown in the U.S. Results show that there were widespread decreases in anthropogenic (e.g., NOx) emissions in the U.S. during March-June 2020, which led to widespread decreases in ozone concentrations in the rural regions that are NOx-limited, but also some localized increases near urban centers that are VOC-limited. Later in June-September, there were smaller decreases, and potentially some relative increases in NOx emissions for many areas of the U.S. (e.g., south-southeast) that led to more extensive increases in ozone concentrations that are partly in agreement with observations. The widespread NOx emissions changes also alters the O3 photochemical formation regimes, most notably the NOx emissions decreases in March-April, which can enhance (mitigate) the NOx-limited (VOC-limited) regimes in different regions of CONUS. The average of all AirNow hourly O3 changes for 2020-2019 range from about +1 to -4 ppb during March-September, and are associated with predominantly urban monitoring sites that demonstrate considerable spatiotemporal variability for the 2020 ozone changes compared to the previous five years individually (2015-2019). The simulated maximum values of the average O3 changes for March-September range from about +8 to -4 ppb (or +40 to -10%). Results of this work have implications for the use of widespread controls of anthropogenic emissions, particularly those from mobile sources, used to curb ozone pollution under the current meteorological and climate conditions in the U.S.

Satellite Monitoring for Air Quality and Health.

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016-2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 µm in diameter (PM2.5) and nitrogen dioxide (NO2). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

Evaluation of the offline-coupled GFSv15-FV3-CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States.

As a candidate for the next-generation National Air Quality Forecast Capability (NAQFC), the meteorological forecast from the Global Forecast System with the new Finite Volume Cube-Sphere dynamical core (GFS-FV3) will be applied to drive the chemical evolution of gases and particles described by the Community Multiscale Air Quality modeling system. CMAQv5.0.2, a historical version of CMAQ, has been coupled with the North American Mesoscale Forecast System (NAM) model in the current operational NAQFC. An experimental version of the NAQFC based on the offline-coupled GFS-FV3 version 15 with CMAQv5.0.2 modeling system (GFSv15-CMAQv5.0.2) has been developed by the National Oceanic and Atmospheric Administration (NOAA) to provide real-time air quality forecasts over the contiguous United States (CONUS) since 2018. In this work, comprehensive region-specific, time-specific, and categorical evaluations are conducted for meteorological and chemical forecasts from the offline-coupled GFSv15-CMAQv5.0.2 for the year 2019. The forecast system shows good overall performance in forecasting meteorological variables with the annual mean biases of -0.2 °C for temperature at 2 m, 0.4% for relative humidity at 2 m, and 0.4 m s-1 for wind speed at 10 m compared to the METeorological Aerodrome Reports (METAR) dataset. Larger biases occur in seasonal and monthly mean forecasts, particularly in spring. Although the monthly accumulated precipitation forecasts show generally consistent spatial distributions with those from the remote-sensing and ensemble datasets, moderate-to-large biases exist in hourly precipitation forecasts compared to the Clean Air Status and Trends Network (CASTNET) and METAR. While the forecast system performs well in forecasting ozone (O3) throughout the year and fine particles with a diameter of 2.5 µm or less (PM2.5) for warm months (May-September), it significantly overpredicts annual mean concentrations of PM2.5. This is due mainly to the high predicted concentrations of fine fugitive and coarse-mode particle components. Underpredictions in the southeastern US and California during summer are attributed to missing sources and mechanisms of secondary organic aerosol formation from biogenic volatile organic compounds (VOCs) and semivolatile or intermediate-volatility organic compounds. This work demonstrates the ability of FV3-based GFS in driving the air quality forecasting. It identifies possible underlying causes for systematic region- and time-specific model biases, which will provide a scientific basis for further development of the next-generation NAQFC.

Phase Transitions in Poly(vinylidene fluoride)/Polymethylene-Based Diblock Copolymers and Blends.

The crystallization and morphology of two linear diblock copolymers based on polymethylene (PM) and poly(vinylidene fluoride) (PVDF) with compositions PM23-b-PVDF77 and PM38-b-PVDF62 (where the subscripts indicate the relative compositions in wt%) were compared with blends of neat components with identical compositions. The samples were studied by SAXS (Small Angle X-ray Scattering), WAXS (Wide Angle X-ray Scattering), PLOM (Polarized Light Optical Microscopy), TEM (Transmission Electron Microscopy), DSC (Differential Scanning Calorimetry), BDS (broadband dielectric spectroscopy), and FTIR (Fourier Transform Infrared Spectroscopy). The results showed that the blends are immiscible, while the diblock copolymers are miscible in the melt state (or very weakly segregated). The PVDF component crystallization was studied in detail. It was found that the polymorphic structure of PVDF was a strong function of its environment. The number of polymorphs and their amount depended on whether it was on its own as a homopolymer, as a block component in the diblock copolymers or as an immiscible phase in the blends. The cooling rate in non-isothermal crystallization or the crystallization temperature in isothermal tests also induced different polymorphic compositions in the PVDF crystals. As a result, we were able to produce samples with exclusive ferroelectric phases at specific preparation conditions, while others with mixtures of paraelectric and ferroelectric phases.

Long Term Real-World Outcomes of Trifluridine/Tipiracil in Metastatic Colorectal Cancer-A Single UK Centre Experience.

In the UK, Trifluridine-tipiracil (Lonsurf) is used to treat metastatic colorectal cancer in the third-line setting, after prior exposure to fluoropyrimidine-based regimes. Current data on the real-world use of Lonsurf lack long-term follow-up data. A retrospective evaluation of patients receiving Lonsurf at our Cancer Centre in 2016-2017 was performed, all with a minimum of two-year follow-up. Fifty-six patients were included in the review. The median number of cycles of Lonsurf administered was 3. Median follow-up was 6.0 months, with all patients deceased at the time of analysis. Median progression-free survival (PFS) was 3.2 months, and overall survival (OS) was 5.8 months. The median interval from Lonsurf discontinuation to death was two months, but seven patients received further systemic treatment and median OS gained was 12 months. Lonsurf offered a slightly better PFS but inferior OS to that of the RECOURSE trial, with PFS similar to real-world data previously presented. Interestingly, 12.5% had a PFS > 9 months, and this cohort had primarily left-sided and RAS wild-type disease. A subset received further systemic treatment on Lonsurf discontinuation with good additional OS benefit. Lonsurf may alter the course of disease for a subset of patients, and further treatment on progression can be considered in carefully selected patients.