Photocatalytic chlorine atom production on mineral dust-sea spray aerosols over the North Atlantic.

Active chlorine in the atmosphere is poorly constrained and so is its role in the oxidation of the potent greenhouse gas methane, causing uncertainty in global methane budgets. We propose a photocatalytic mechanism for chlorine atom production that occurs when Sahara dust mixes with sea spray aerosol. The mechanism is validated by implementation in a global atmospheric model and thereby explaining the episodic, seasonal, and location-dependent 13C depletion in CO in air samples from Barbados [J.E. Mak, G. Kra, T. Sandomenico, P. Bergamaschi, J. Geophys. Res. Atmos. 108 (2003)], which remained unexplained for decades. The production of Cl can also explain the anomaly in the CO:ethane ratio found at Cape Verde [K. A. Read et al., J. Geophys. Res. Atmos. 114 (2009)], in addition to explaining the observation of elevated HOCl [M. J. Lawler et al., Atmos. Chem. Phys. 11, 7617-7628 (2011)]. Our model finds that 3.8 Tg(Cl) y-1 is produced over the North Atlantic, making it the dominant source of chlorine in the region; globally, chlorine production increases by 41%. The shift in the methane sink budget due to the increased role of Cl means that isotope-constrained top-down models fail to allocate 12 Tg y-1 (2% of total methane emissions) to 13C-depleted biological sources such as agriculture and wetlands. Since 2014, an increase in North African dust emissions has increased the 13C isotope of atmospheric CH4, thereby partially masking a much greater decline in this isotope, which has implications for the interpretation of the drivers behind the recent increase of methane in the atmosphere.

A Pilot Study of Pembrolizumab in Combination With Y90 Radioembolization in Subjects With Poor Prognosis Hepatocellular Carcinoma.

BACKGROUND: Combination checkpoint inhibition therapy with yttrium-90 (Y90) radioembolization represents an emerging area of interest in the treatment of advanced hepatocellular carcinoma (HCC). HCRN GI15-225 is an open-label, single-arm multicenter, pilot study (NCT03099564). METHODS: Eligible patients had poor prognosis, localized HCC defined as having portal vein thrombus, multifocal disease, and/or diffuse disease that were not eligible for liver transplant or surgical resection. Patients received pembrolizumab 200 mg intravenously every 3 weeks in conjunction with glass yttrium-90 (Y90) radioembolization TheraSphere. Primary endpoint was 6-month progression-free survival (PFS6) per RECIST 1.1. Secondary endpoints included time to progression (TTP), objective response rate (ORR), overall survival (OS), and safety/tolerability. RESULTS: Between October 23, 2017 and November 24, 2020, 29 patients were enrolled: 2 were excluded per protocol. Fifteen of the remaining 27 patients were free of progression at 6 months (55.6%; 95% CI, 35.3-74.5) with median PFS 9.95 months (95% CI, 4.14-15.24) and OS 27.30 months (95% CI, 10.15-39.52). One patient was not evaluable for response due to death; among the remaining 26 patients, ORR was 30.8% (95% CI, 14.3-51.8) and DCR was 84.6% (95% CI, 65.1-95.6). CONCLUSION: In patients with localized, poor prognosis HCC, pembrolizumab in addition to glass Y90 radioembolization demonstrated promising efficacy and safety consistent with prior observations (ClinicalTrials.gov Identifier: NCT03099564; IRB Approved: 16-3255 approved July 12, 2016).

Short-Term Out-of-Pocket and Total Costs of Care After Ablation, Resection, or Transplant for Early-Stage Hepatocellular Carcinoma: A National SEER-Medicare Cost Comparison.

Background: Differences in survival and morbidity among treatment options (ablation, surgical resection, and transplant) for early-stage hepatocellular carcinoma (HCC) have been well-studied. Additional understanding of the costs of such care would help to identify drivers of high costs and potential barriers to care delivery. Objective: To quantify total and patient out-of-pocket costs for ablation, surgical resection, and transplant in the management of early-stage HCC and to identify factors predictive of these costs. Methods: This retrospective U.S. population-based study used the SEER-Medicare linked dataset to identify a sample of 1067 Medicare beneficiaries (mean age, 73 years; 674 men, 393 women) diagnosed with early-stage HCC (size ≤5 cm) treated with ablation (N=623), resection (N=201), or transplant (N=243) between January 2009 and December 2016. Total costs and patient out-of-pocket costs for the index procedure as well as for any care within 30 days and 90 days post-procedure were identified and stratified by treatment modality. Additional comparisons were performed among propensity-score matched subgroups of patients treated by ablation or resection (each N=172). Multivariable linear regression models were used to identify factors predictive of total costs and out-of-pocket costs for index procedures as well as for 30-day and 90-day post-procedure periods. Results: For ablation, resection, and transplant, median index-procedure total cost was $6689, $25,614, and $66,034; index-procedure out-of-pocket cost was $1235, $1650, and $1317; 30-day total cost was $9456, $29,754, and $69,856; 30-day out-of-pocket cost was $1646, $2208, and $3198; 90-day total cost was $14,572, $34,984, and $88,103; and 90-day out-of-pocket cost was $2138, $2462, and $3876, respectively (all p<.001). In propensity-matched subgroups, ablation and resection had median index-procedure, 30-day, and 90-day total costs of $6690 and $25,716, $9995 and $30,365, and $15,851 and $34,455, respectively. In multivariable analysis adjusting for socioeconomic factors, comorbidities, and liver-disease prognostic indicators, surgical treatment (resection or transplant) was predictive of significantly greater costs compared with ablation at all time points. Conclusion: Total and out-of-pocket costs for index procedures as well as for 30-day and 90-day post-procedure periods were lowest for ablation, followed by resection and then transplant. Clinical Impact: This comprehensive cost analysis could help inform future cost-effectiveness analyses.

Diffusion-Limited Kinetics in Reactive Systems.

A proper representation of chemical kinetics is vital to understanding, modeling, and optimizing many important chemical processes. In liquid and surface phases, where diffusion is slow, the rate at which the reactants diffuse together limits the overall rate of many elementary reactions. Commonly, the textbook Smoluchowski theory is utilized to estimate effective rate coefficients in the liquid phase. On surfaces, modelers commonly resort to much more complex and expensive Kinetic Monte Carlo (KMC) simulations. Here, we extend the Smoluchowski model to allow the diffusing species to undergo chemical reactions and derive analytical formulas for the diffusion-limited rate coefficients for 3D, 2D, and 2D/3D interface cases. With these equations, we are able to demonstrate that when species react faster than they diffuse they can react orders of magnitude faster than predicted by Smoluchowski theory, through what we term "the reactive transport effect". We validate the derived steady-state equations against particle Monte Carlo (PMC) simulations, KMC simulations, and non-steady-state solutions. Furthermore, using PMC and KMC simulations, we propose corrections that agree with all limits and the computed data for the 2D and 2D/3D interface steady-state equations, accounting for unique limitations in the associated derived equations. Additionally, we derive equations to handle couplings between diffusion-limited rate coefficients in reaction networks. We believe these equations should make it possible to run much more accurate mean-field simulations of liquids, surfaces, and liquid-surface interfaces accounting for diffusion limitations and the reactive transport effect.

Subgraph Isomorphic Decision Tree to Predict Radical Thermochemistry with Bounded Uncertainty Estimation.

Detailed chemical kinetic models offer valuable mechanistic insights into industrial applications. Automatic generation of reliable kinetic models requires fast and accurate radical thermochemistry estimation. Kineticists often prefer hydrogen bond increment (HBI) corrections from a closed-shell molecule to the corresponding radical for their interpretability, physical meaning, and facilitation of error cancellation as a relative quantity. Tree estimators, used due to limited data, currently rely on expert knowledge and manual construction, posing challenges in maintenance and improvement. In this work, we extend the subgraph isomorphic decision tree (SIDT) algorithm originally developed for rate estimation to estimate HBI corrections. We introduce a physics-aware splitting criterion, explore a bounded weighted uncertainty estimation method, and evaluate aleatoric uncertainty-based and model variance reduction-based prepruning methods. Moreover, we compile a data set of thermochemical parameters for 2210 radicals involving C, O, N, and H based on quantum chemical calculations from recently published works. We leverage the collected data set to train the SIDT model. Compared to existing empirical tree estimators, the SIDT model (1) offers an automatic approach to generating and extending the tree estimator for thermochemistry, (2) has better accuracy and R2, (3) provides significantly more realistic uncertainty estimates, and (4) has a tree structure much more advantageous in descent speed. Overall, the SIDT estimator marks a great leap in kinetic modeling, offering more precise, reliable, and scalable predictions for radical thermochemistry.

Carbon uptake in Eurasian boreal forests dominates the high-latitude net ecosystem carbon budget.

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003-2015) vegetation gross primary productivity (GPP), ecosystem respiration (Reco ), net ecosystem CO2 exchange (NEE; Reco - GPP), and terrestrial methane (CH4 ) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km2 flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of -850 Tg CO2 -C year-1 . Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH4 emissions from tundra and boreal wetlands (not accounting for aquatic CH4 ) were estimated at 35 Tg CH4 -C year-1 . Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.

Challenges, Barriers, and Successes of Standardized Report Templates: Results of a Society of Interventional Radiology Survey.

Registry data are being increasingly used to establish treatment guidelines, set benchmarks, allocate resources, and make payment decisions. Although many registries rely on manual data entry, the Society of Interventional Radiology (SIR) is using automated data extraction for its VIRTEX registry. This process relies on participants using consistent terminology with highly structured data in physician-developed standardized reports (SR). To better understand barriers to adoption, a survey was sent to 3,178 SIR members. Responses were obtained from 451 interventional radiology practitioners (14.2%) from 92 unique academic and 151 unique private practices. Of these, 75% used structured reports and 32% used the SIR SR. The most common barriers to the use of these reports include SR length (35% of respondents), lack of awareness about the SR (31%), and lack of agreement on adoption within practices (27%). The results demonstrated insights regarding barriers in the use and/or adoption of SR and potential solutions.

Predicting the Safety and Effectiveness of Inferior Vena Cava Filters (PRESERVE): Outcomes at 12 months.

OBJECTIVE: To determine the safety and effectiveness of vena cava filters (VCFs). METHODS: A total of 1429 participants (62.7 ± 14.7 years old; 762 [53.3% male]) consented to enroll in this prospective, nonrandomized study at 54 sites in the United States between October 10, 2015, and March 31, 2019. They were evaluated at baseline and at 3, 6, 12, 18, and 24 months following VCF implantation. Participants whose VCFs were removed were followed for 1 month after retrieval. Follow-up was performed at 3, 12, and 24 months. Predetermined composite primary safety (freedom from perioperative serious adverse events [AEs] and from clinically significant perforation, VCF embolization, caval thrombotic occlusion, and/or new deep vein thrombosis [DVT] within 12-months) and effectiveness (composite comprising procedural and technical success and freedom from new symptomatic pulmonary embolism [PE] confirmed by imaging at 12-months in situ or 1 month postretrieval) end points were assessed. RESULTS: VCFs were implanted in 1421 patients. Of these, 1019 (71.7%) had current DVT and/or PE. Anticoagulation therapy was contraindicated or had failed in 1159 (81.6%). One hundred twenty-six (8.9%) VCFs were prophylactic. Mean and median follow-up for the entire population and for those whose VCFs were not removed was 243.5 ± 243.3 days and 138 days and 332.6 ± 290 days and 235 days, respectively. VCFs were removed from 632 (44.5%) patients at a mean of 101.5 ± 72.2 days and median 86.3 days following implantation. The primary safety end point and primary effectiveness end point were both achieved. Procedural AEs were uncommon and usually minor, but one patient died during attempted VCF removal. Excluding strut perforation greater than 5 mm, which was demonstrated on 31 of 201 (15.4%) patients' computed tomography scans available to the core laboratory, and of which only 3 (0.2%) were deemed clinically significant by the site investigators, VCF-related AEs were rare (7 of 1421, 0.5%). Postfilter, venous thromboembolic events (none fatal) occurred in 93 patients (6.5%), including DVT (80 events in 74 patients [5.2%]), PE (23 events in 23 patients [1.6%]), and/or caval thrombotic occlusions (15 events in 15 patients [1.1%]). No PE occurred in patients following prophylactic placement. CONCLUSIONS: Implantation of VCFs in patients with venous thromboembolism was associated with few AEs and with a low incidence of clinically significant PEs.

Beyond Survival: Adverse Events and Care Delivery Outcomes after Early Liver Cancer Treatment in a Nationally Representative Cohort.

PURPOSE: To compare secondary outcomes after ablation (AB), surgical resection (SR), and liver transplant (LT) for small hepatocellular carcinomas (HCCs), including resource utilization and adverse event (AE) rates. MATERIALS AND METHODS: Using Surveillance, Epidemiology, and End Results Program (SEER)-Medicare, HCCs <5 cm that were treated with AB, SR, or LT in 2009-2016 (n = 1,067) were identified using Healthcare Common Procedure Coding System codes through Medicare claims. Index procedure length of stay, need for intensive care unit (ICU) level care, readmission rates, and AE rates at 30 and 90 days were compared using chi-square tests or Fisher exact tests. Examined AEs included hemorrhage, abscess formation, biliary injury, pneumonia, sepsis, liver disease-related AEs, liver failure, and anesthesia-related AEs, identified by International Classification of Diseases, Ninth/10th Revision, codes. RESULTS: The median length of stay for initial treatment was 1 day, 6 days, and 7 days for AB, SR, and LT, respectively (P < .001). During initial hospital stay, 5.0%, 40.8%, and 63.4% of AB, SR, and LT cohorts, respectively, received ICU-level care (P < .001). By 30 and 90 days, there were significant differences among the AB, SR, and LT cohorts in the rate of postprocedural hemorrhage, abscess formation, biliary injury, pneumonia, sepsis, liver disease-related AEs, and anesthesia-related AEs (P < .05). By 90 days, the readmission rates after AB, SR, and LT were 18.6%, 28.2%, and 40.6% (P < .001), respectively. CONCLUSIONS: AB results in significantly less healthcare utilization during the initial 90 days after procedure compared with that after SR and LT due to shorter length of stay, lower intensity care, fewer readmissions, and fewer AEs.

Pynta─An Automated Workflow for Calculation of Surface and Gas-Surface Kinetics.

Many important industrial processes rely on heterogeneous catalytic systems. However, given all possible catalysts and conditions of interest, it is impractical to optimize most systems experimentally. Automatically generated microkinetic models can be used to efficiently consider many catalysts and conditions. However, these microkinetic models require accurate estimation of many thermochemical and kinetic parameters. Manually calculating these parameters is tedious and error prone, involving many interconnected computations. We present Pynta, a workflow software for automating the calculation of surface and gas-surface reactions. Pynta takes the reactants, products, and atom maps for the reactions of interest, generates sets of initial guesses for all species and saddle points, runs all optimizations, frequency, and IRC calculations, and computes the associated thermochemistry and rate coefficients. It is able to consider all unique adsorption configurations for both adsorbates and saddle points, allowing it to handle high index surfaces and bidentate species. Pynta implements a new saddle point guess generation method called harmonically forced saddle point searching (HFSP). HFSP defines harmonic potentials based on the optimized adsorbate geometries and which bonds are breaking and forming that allow initial placements to be optimized using the GFN1-xTB semiempirical method to create reliable saddle point guesses. This method is reaction class agnostic and fast, allowing Pynta to consider all possible adsorbate site placements efficiently. We demonstrate Pynta on 11 diverse reactions involving monodenate, bidentate, and gas-phase species, many distinct reaction classes, and both a low and a high index facet of Cu. Our results suggest that it is very important to consider reactions between adsorbates adsorbed in all unique configurations for interadsorbate group transfers and reactions on high index surfaces.

Constraining China's land carbon sink from emerging satellite CO2 observations: Progress and challenges.

Land carbon sink is a vital component for the achievement of China's ambitious carbon neutrality goal, but its magnitude is poorly known. Atmospheric observations and inverse models are valuable tools to constrain the China's land carbon sink. Space-based CO2 measurements from satellites form an emerging data stream for application of such atmospheric inversions. Here, we reviewed the satellite missions that is dedicated to the monitoring of CO2 , and the recent progresses on the inversion of China's land carbon sink using satellite CO2 measurements. We summarized the limitations and challenges in current space platforms, retrieval algorithms, and the inverse modeling. It is shown that there are large uncertainties of contemporary satellite-based estimates of China's land carbon sink. We discussed future opportunities of continuous improvements in three aspects to better constrain China's land carbon sink with space-based CO2 measurements.

Examining the accuracy of methods for obtaining pressure dependent rate coefficients.

The full energy-grained master equation (ME) is too large to be conveniently used in kinetic modeling, so almost always it is replaced by a reduced model using phenomenological rate coefficients. The accuracy of several methods for obtaining these pressure-dependent phenomenological rate coefficients, and so for constructing a reduced model, is tested against direct numerical solutions of the full ME, and the deviations are sometimes quite large. An algebraic expression for the error between the popular chemically-significant eigenvalue (CSE) method and the exact ME solution is derived. An alternative way to compute phenomenological rate coefficients, simulation least-squares (SLS), is presented. SLS is often about as accurate as CSE, and sometimes has significant advantages over CSE. One particular variant of SLS, using the matrix exponential, is as fast as CSE, and seems to be more robust. However, all of the existing methods for constructing reduced models to approximate the ME, including CSE and SLS, are inaccurate under some conditions, and sometimes they fail dramatically due to numerical problems. The challenge of constructing useful reduced models that more reliably emulate the full ME solution is discussed.

RMG Database for Chemical Property Prediction.

The Reaction Mechanism Generator (RMG) database for chemical property prediction is presented. The RMG database consists of curated datasets and estimators for accurately predicting the parameters necessary for constructing a wide variety of chemical kinetic mechanisms. These datasets and estimators are mostly published and enable prediction of thermodynamics, kinetics, solvation effects, and transport properties. For thermochemistry prediction, the RMG database contains 45 libraries of thermochemical parameters with a combination of 4564 entries and a group additivity scheme with 9 types of corrections including radical, polycyclic, and surface absorption corrections with 1580 total curated groups and parameters for a graph convolutional neural network trained using transfer learning from a set of >130 000 DFT calculations to 10 000 high-quality values. Correction schemes for solvent-solute effects, important for thermochemistry in the liquid phase, are available. They include tabulated values for 195 pure solvents and 152 common solutes and a group additivity scheme for predicting the properties of arbitrary solutes. For kinetics estimation, the database contains 92 libraries of kinetic parameters containing a combined 21 000 reactions and contains rate rule schemes for 87 reaction classes trained on 8655 curated training reactions. Additional libraries and estimators are available for transport properties. All of this information is easily accessible through the graphical user interface at https://rmg.mit.edu. Bulk or on-the-fly use can be facilitated by interfacing directly with the RMG Python package which can be installed from Anaconda. The RMG database provides kineticists with easy access to estimates of the many parameters they need to model and analyze kinetic systems. This helps to speed up and facilitate kinetic analysis by enabling easy hypothesis testing on pathways, by providing parameters for model construction, and by providing checks on kinetic parameters from other sources.

Perturbation of the UV transitions of formaldehyde by TiO2 photocatalysts and Aun nanoclusters.

In the gas phase, formaldehyde has an electric-dipole forbidden transition that becomes allowed by vibronic coupling. In this paper we explore whether perturbation by surfaces could also enhance light absorption by CH2O. We investigate the electronic transitions of formaldehyde in the gas phase and interacting with rutile (110) TiO2, Aun nanoclusters, and Aun on (110)-TiO2. These surfaces are chosen as being representative of metals and metal-oxide minerals, and also because of specific interest in photocatalysts and noble metal nanocluster catalysts. The oscillator strength of the forbidden n → π* transition of formaldehyde in vacuum is investigated by modelling vibrational coupling to the electronic transition with equation-of-motion coupled cluster theory. The excitation energies and oscillator strengths of formaldehyde are calculated for different orientations and distances to the surfaces using the coupled cluster singles and doubles linear response method within the Quantum Mechanical and Molecular Mechanical (QM/MM) model using the aug-cc-pVTZ basis set and compared with the values calculated in vacuo. The electronic transitions of formaldehyde vary very little when placed near a pure TiO2-surface with only minor variations depending on the orientation of formaldehyde. Introducing a gold nanoparticle (by itself or supported by TiO2) induces dramatic changes in the absorption properties. This is due to vibronic interactions and the effect of the broken symmetry on the n → π* transition. We see a large redshift in the transition of 90 nm and oscillator strengths larger than 1.0 × 10-4 for CH2O interacting with Aun.

Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation.

In chemical kinetics research, kinetic models containing hundreds of species and tens of thousands of elementary reactions are commonly used to understand and predict the behavior of reactive chemical systems. Reaction Mechanism Generator (RMG) is a software suite developed to automatically generate such models by incorporating and extrapolating from a database of known thermochemical and kinetic parameters. Here, we present the recent version 3 release of RMG and highlight improvements since the previously published description of RMG v1.0. Most notably, RMG can now generate heterogeneous catalysis models in addition to the previously available gas- and liquid-phase capabilities. For model analysis, new methods for local and global uncertainty analysis have been implemented to supplement first-order sensitivity analysis. The RMG database of thermochemical and kinetic parameters has been significantly expanded to cover more types of chemistry. The present release includes parallelization for faster model generation and a new molecule isomorphism approach to improve computational performance. RMG has also been updated to use Python 3, ensuring compatibility with the latest cheminformatics and machine learning packages. Overall, RMG v3.0 includes many changes which improve the accuracy of the generated chemical mechanisms and allow for exploration of a wider range of chemical systems.

Chemistry and Photochemistry of Pyruvic Acid at the Air-Water Interface.

Interfacial regions are unique chemical reaction environments that can promote chemistry not found elsewhere. The air-water interface is ubiquitous in the natural environment in the form of ocean surfaces and aqueous atmospheric aerosols. Here we investigate the chemistry and photochemistry of pyruvic acid (PA), a common environmental species, at the air-water interface and compare it to its aqueous bulk chemistry using two different experimental setups: (1) a Langmuir-Blodgett trough, which models natural water surfaces and provides a direct comparison between the two reaction environments, and (2) an atmospheric simulation chamber (CESAM) to monitor the chemical processing of nebulized aqueous PA droplets. The results show that surface chemistry leads to substantial oligomer formation. The sequence begins with the condensation of lactic acid (LA), formed at the surface, with itself and with pyruvic acid, and LA + LA - H2O and LA + PA - H2O are prominent among the products in addition to a series of higher-molecular-weight oligomers of mixed units of PA and LA. In addition, we see zymonic acid at the surface. Actinic radiation enhances the production of the oligomers and produces additional surface-active molecules known from the established aqueous photochemical mechanisms. The presence and formation of complex organic molecules at the air-water interface from a simple precursor like PA in the natural environment is relevant to contemporary atmospheric science and is important in the context of prebiotic chemistry, where abiotic production of complex molecules is necessary for abiogenesis.

Improving Estimates of PM2.5 Concentration and Chemical Composition by Application of High Spectral Resolution Lidar (HSRL) and Creating Aerosol Types from Chemistry (CATCH) Algorithm.

Improved characterization of ambient PM2.5 mass concentration and chemical speciation is a topic of interest in air quality and climate sciences. Over the past decades, considerable efforts have been made to improve ground-level PM2.5 using remotely sensed data. Here we present two new approaches for estimating atmospheric PM2.5 and chemical composition based on the High Spectral Resolution Lidar (HSRL)-retrieved aerosol extinction values and types and Creating Aerosol Types from Chemistry (CATCH)-derived aerosol chemical composition. The first methodology (CMAQ-HSRL-CH) improves EPA's Community Multiscale Air Quality (CMAQ) predictions by applying variable scaling factors derived using remotely-sensed information about aerosol vertical distribution and types and the CATCH algorithm. The second methodology (HSRL-CH) does not require regional model runs and can provide atmospheric PM2.5 mass concentration and chemical speciation using only the remotely sensed data and the CATCH algorithm. The resulting PM2.5 concentrations and chemical speciation derived for NASA DISCOVER-AQ (Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality) Baltimore-Washington, D.C. Corridor (BWC) Campaign (2011) are compared to surface measurements from EPA's Air Quality Systems (AQS) network. The analysis shows that the CMAQ-HSRL-CH method leads to considerable improvement of CMAQ's predicted PM2.5 concentrations (R2 value increased from 0.37 to 0.63, the root mean square error (RMSE) was reduced from 11.9 to 7.2 µg m-3, and the normalized mean bias (NMB) was lowered from -46.0 to 4.6%). The HSRL-CH method showed statistics (R2=0.75, RMSE=8.6 µgm-3, and NMB=24.0%), which were better than the CMAQ prediction of PM2.5 alone and analogous to CMAQ-HSRL-CH. In addition to mass concentration, HSRL-CH can also provide aerosol chemical composition without specific model simulations. We expect that the HSRL-CH method will be able to make reliable estimates of PM2.5 concentration and chemical composition where HSRL data are available.

Society of Interventional Radiology Clinical Practice Guideline for Inferior Vena Cava Filters in the Treatment of Patients with Venous Thromboembolic Disease: Developed in collaboration with the American College of Cardiology, American College of Chest Physicians, American College of Surgeons Committee on Trauma, American Heart Association, Society for Vascular Surgery, and Society for Vascular Medicine.

PURPOSE: To provide evidence-based recommendations on the use of inferior vena cava (IVC) filters in the treatment of patients with or at substantial risk of venous thromboembolic disease. MATERIALS AND METHODS: A multidisciplinary expert panel developed key questions to address in the guideline, and a systematic review of the literature was conducted. Evidence was graded based on a standard methodology, which was used to inform the development of recommendations. RESULTS: The systematic review identified a total of 34 studies that provided the evidence base for the guideline. The expert panel agreed on 18 recommendations. CONCLUSIONS: Although the evidence on the use of IVC filters in patients with or at risk of venous thromboembolic disease varies in strength and quality, the panel provides recommendations for the use of IVC filters in a variety of clinical scenarios. Additional research is needed to optimize care for this patient population.

Final Two-Year Outcomes for the Sentry Bioconvertible Inferior Vena Cava Filter in Patients Requiring Temporary Protection from Pulmonary Embolism.

PURPOSE: To report final 2-year outcomes with the Sentry bioconvertible inferior vena cava (IVC) filter in patients requiring temporary protection against pulmonary embolism (PE). MATERIALS AND METHODS: In a prospective multicenter trial, the Sentry filter was implanted in 129 patients with documented deep vein thrombosis (DVT) and/or PE (67.5%) or who were at temporary risk of developing DVT/PE (32.6%). Patients were monitored and bioconversion status ascertained by radiography, computed tomography (CT), and CT venography through 2 years. RESULTS: The composite primary 6-month endpoint of clinical success was achieved in 97.4% (111/114) of patients. The rate of new symptomatic PE was 0% (n = 126) through 1 year and 2.4% (n = 85) through the second year of follow-up, with 2 new nonfatal cases at 581 and 624 days that were adjudicated as not related to the procedure or device. Two patients (1.6%) developed symptomatic caval thrombosis during the first month and underwent successful interventions without recurrence. No other filter-related symptomatic complications occurred through 2 years. There was no filter tilting, migration, embolization, fracture, or caval perforation and no filter-related deaths through 2 years. Filter bioconversion was successful for 95.7% (110/115) of patients at 6 months, 96.4% (106/110) of patients at 12 months, and 96.5% (82/85) of patients at 24 months. Through 24 months of follow-up, there was no evidence of late-stage IVC obstruction or thrombosis after filter bioconversion or of thrombogenicity associated with retracted filter arms. CONCLUSIONS: The Sentry IVC filter provided safe and effective protection against PE, with a high rate of intended bioconversion and a low rate of device-related complications, through 2 years of follow-up.