Development of a fast, urban chemistry metamodel for inclusion in global models

A reduced form metamodel has been produced to simulate the effects of physical, chemical, and meteorological processing of highly reactive trace species in urban areas, which is capable of efficiently simulating the urban concentration, surface deposition, and net export flux of these species. A polynomial chaos expansion and the probabilistic collocation method have been used to develop the metamodel, and its coefficients, so that it is applicable under a broad range of present-day and future conditions. The inputs upon which this metamodel have been formed are based on a combination of physical properties (average temperature, diurnal temperature range, date, and latitude), anthropogenic properties (patterns and amounts of emissions), and the nature of the surrounding environment (background concentrations of species). The metamodel development involved using probability distribution functions (PDFs) of the inputs to run a detailed parent chemical and physical model, the Comprehensive Air Quality Model with Extensions (CAMx), thousands of times. Outputs from these runs were used in turn to both determine the coefficients of and test the precision of the metamodel, as compared with the detailed parent model. It was determined that the deviations between the metamodel and the parent mode for many important species (O[subscript 3], CO, NO[subscript x], and black carbon (BC)) were found to have a weighted RMS error less than 10 % in all cases, with many of the specific cases having a weighted RMS error less than 1 %. Some of the other important species (VOCs, PAN, OC, and sulfate aerosol) usually have their weighted RMS error less than 10 % as well, except for a small number of cases. In these cases, the complexity and non-linearity of the physical, chemical, and meteorological processing is too large for the third order metamodel to give an accurate fit. Finally, sensitivity tests have been performed, to observe the response of the 16 metamodels (4 different meteorologies and 4 different urban types) to a broad set of potential inputs. These results were compared with observations of ozone, CO, formaldehyde, BC, and PM[subscript 10] from a few well observed urban areas, and in most of the cases, the output distributions were found to be within ranges of the observations. Overall, a set of efficient and robust metamodels have been generated which are capable of simulating the effects of various physical, chemical, and meteorological processing, and capable of determining the urban concentrations, mole fractions, and fluxes of species, important to human health and the global climate.Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global ChangeUnited States. Dept. of Energy. Office of Biological and Environmental Research (grant DE-FG02-94ER61937)United States. Dept. of Energy. Office of Biological and Environmental Research (grant DE-FG02-93ER61677

Urban-scale impacts on the global-scale composition and climate effects of anthropogenic aerosols

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 247-256).A reduced form meta model has been produced to simulate the effects of physical, chemical, and meteorological processing of highly reactive trace species in hypothetical urban areas, which is capable of efficiently simulating the urban concentration, surface deposition, and net mass flux of these species. A polynomial chaos expansion and the probabilistic collocation method have been used for the metamodel, and its coefficients were fit so as to be applicable under a broad range of present-day and future conditions. The inputs upon which this metamodel have been formed are based on a combination of physical properties (average temperature, diurnal temperature range, date, and latitude), anthropogenic properties (patterns and amounts of emissions), and the surrounding environment (background concentrations of certain species). Probability Distribution Functions (PDFs) of the inputs were used to run a detailed parent chemical and physical model, the Comprehensive Air Quality Model with Extensions (CAMx), thousands of times. Outputs from these runs were used in turn to both determine the coefficients of and test the precision of the metamodel, as compared with the detailed parent model. The deviations between the metamodel and the parent mode for many important species (03, CO, NO2, and BC) were found to have a weighted RMS error less than 10% in all cases, with many of the specific cases having a weighted RMS error less than 1%. Some of the other important species (VOCs, PAN, OC, and sulfate aerosol) usually have their weighted RMS error less than 10% as well, except for a small number of cases. These cases, in which the highly non-linear nature of the processing is too large for the third order metamodel to give an accurate fit, are explained in terms of the complexity and non-linearity of the physical, chemical, and meteorological processing. In addition, for those species in which good fits have not been obtained, the program has been designed in such a way that values which are not physically realistic are flagged. Sensitivity tests have been performed, to observe the response of the 16 metamodels (4 different meteorologies and 4 different urban types) to a broad set of potential inputs. These results were compared with observations of 03, CO, formaldehyde, BC, and PM10 from a few well observed urban areas, and in most of the cases, the output distributions were found to be within ranges of the observations. Overall, a set of efficient and robust metamodels have been generated which are capable of simulating the effects of various physical, chemical, and meteorological processing, and capable of determining the urban concentrations, mole fractions, and fluxes of species, important to human health and the climate. The point of developing these computationally efficient metamodels of urban processing is so that they can be used in the context of global modeling efforts. In specific, urban-scale processing has long been excluded in global 3D chemical transport models due to its large computational demands. In this thesis, the metamodel is used to simulate this processing, and compare a set of results against the more traditional approach of dilution of emissions into large grid boxes. This metamodel provides a tool to simulate, in a global 3D model, the effects of cities around the world on aerosol chemistry, physics, and radiative effects at the global scale. It is then demonstrated that a significant Bias Error = (Dilution Approach - Urban Processing) / Urban Processing is incurred due to the ignoring of urban processing. Specifically, the globally averaged monthly minimum, monthly maximum, and monthly average bias error caused by ignoring urban processing on the total aerosol surface concentration (+0.23, +0.28, and +0.26), the total aerosol column abundance (+0.43, +0.61, and +0.51), the AOD (+0.35, +0.50, and +0.42), and the AAOD (+0.01, +0.18, and +0.09), respectively. This leads to a significant Error = (Dilution Approach - Urban Processing) for the globally averaged monthly minimum, monthly maximum, and monthly average error for the top of the atmosphere radiative forcing (-0.414, -0.168, and -0.272 W/m 2), the surface radiative forcing (-1.02, -0.352, and -0.448 W/m 2), and the atmospheric radiative forcing (-0.004, +0.849, and +0.176 W/m 2 ), respectively. These results show that failure to consider urban scale processing leads to significantly more negative aerosol radiative forcing in the dilution case, as compared to when detailed urban scale processing is considered.by Jason Blake Cohen.Sc.D

Organic nitrate chemistry and its implications for nitrogen budgets in an isoprene- and monoterpene-rich atmosphere: constraints from aircraft (SEAC4RS) and ground-based (SOAS) observations in the Southeast US

Formation of organic nitrates (RONO2) during oxidation of biogenic volatile organic compounds (BVOCs: isoprene, monoterpenes) is a significant loss pathway for atmospheric nitrogen oxide radicals (NOx), but the chemistry of RONO2 formation and degradation remains uncertain. Here we implement a new BVOC oxidation mechanism (including updated isoprene chemistry, new monoterpene chemistry, and particle uptake of RONO2) in the GEOS-Chem global chemical transport model with  ∼  25  x  25 km2 resolution over North America. We evaluate the model using aircraft (SEAC4RS) and ground-based (SOAS) observations of NOx, BVOCs, and RONO2 from the Southeast US in summer 2013. The updated simulation successfully reproduces the concentrations of individual gas- and particle-phase RONO2 species measured during the campaigns. Gas-phase isoprene nitrates account for 25-50 % of observed RONO2 in surface air, and we find that another 10 % is contributed by gas-phase monoterpene nitrates. Observations in the free troposphere show an important contribution from long-lived nitrates derived from anthropogenic VOCs. During both campaigns, at least 10 % of observed boundary layer RONO2 were in the particle phase. We find that aerosol uptake followed by hydrolysis to HNO3 accounts for 60 % of simulated gas-phase RONO2 loss in the boundary layer. Other losses are 20 % by photolysis to recycle NOx and 15 % by dry deposition. RONO2 production accounts for 20 % of the net regional NOx sink in the Southeast US in summer, limited by the spatial segregation between BVOC and NOx emissions. This segregation implies that RONO2 production will remain a minor sink for NOx in the Southeast US in the future even as NOx emissions continue to decline

Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors

INTRODUCTION COVID-19 became a global pandemic partially as a result of the lack of easily deployable, broad-spectrum oral antivirals, which complicated its containment. Even endemically, and with effective vaccinations, it will continue to cause acute disease, death, and long-term sequelae globally unless there are accessible treatments. COVID-19 is not an isolated event but instead is the latest example of a viral pandemic threat to human health. Therefore, antiviral discovery and development should be a key pillar of pandemic preparedness efforts. RATIONALE One route to accelerate antiviral drug discovery is the establishment of open knowledge bases, the development of effective technology infrastructures, and the discovery of multiple potent antivirals suitable as starting points for the development of therapeutics. In this work, we report the results of the COVID Moonshot—a fully open science, crowdsourced, and structure-enabled drug discovery campaign—against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro). This collaboration may serve as a roadmap for the potential development of future antivirals. RESULTS On the basis of the results of a crystallographic fragment screen, we crowdsourced design ideas to progress from fragment to lead compounds. The crowdsourcing strategy yielded several key compounds along the optimization trajectory, including the starting compound of what became the primary lead series. Three additional chemically distinct lead series were also explored, spanning a diversity of chemotypes. The collaborative and highly automated nature of the COVID Moonshot Consortium resulted in >18,000 compound designs, >2400 synthesized compounds, >490 ligand-bound x-ray structures, >22,000 alchemical free-energy calculations, and >10,000 biochemical measurements—all of which were made publicly available in real time. The recently approved antiviral ensitrelvir was identified in part based on crystallographic data from the COVID Moonshot Consortium. This campaign led to the discovery of a potent [median inhibitory concentration (IC50) = 37 ± 2 nM] and differentiated (noncovalent and nonpeptidic) lead compound that also exhibited potent cellular activity, with a median effective concentration (EC50) of 64 nM in A549-ACE2-TMPRSS2 cells and 126 nM in HeLa-ACE2 cells without measurable cytotoxicity. Although the pharmacokinetics of the reported compound is not yet optimal for therapeutic development, it is a promising starting point for further antiviral discovery and development. CONCLUSION The success of the COVID Moonshot project in producing potent antivirals, building open knowledge bases, accelerating external discovery efforts, and functioning as a useful information-exchange hub is an example of the potential effectiveness of open science antiviral discovery programs. The open science, patent-free nature of the project enabled a large number of collaborators to provide in-kind support, including synthesis, assays, and in vitro and in vivo experiments. By making all data immediately available and ensuring that all compounds are purchasable from Enamine without the need for materials transfer agreements, we aim to accelerate research globally along parallel tracks. In the process, we generated a detailed map of the structural plasticity of Mpro, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data to spur further research into antivirals and discovery methodologies. We hope that this can serve as an alternative model for antiviral discovery and future pandemic preparedness. Further, the project also showcases the role of machine learning, computational chemistry, and high-throughput structural biology as force multipliers in drug design. Artificial intelligence and machine learning algorithms help accelerate chemical synthesis while balancing multiple competing molecular properties. The design-make-test-analyze cycle was accelerated by these algorithms combined with planetary-scale biomolecular simulations of protein-ligand interactions and rapid structure determination

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

Pathological chemotherapy response score is prognostic in tubo-ovarian high-grade serous carcinoma: A systematic review and meta-analysis of individual patient data

There is a need to develop and validate biomarkers for treatment response and survival in tubo-ovarian high-grade serous carcinoma (HGSC). The chemotherapy response score (CRS) stratifies patients into complete/near-complete (CRS3), partial (CRS2), and no/minimal (CRS1) response after neoadjuvant chemotherapy (NACT). Our aim was to review current evidence to determine whether the CRS is prognostic in women with tubo-ovarian HGSC treated with NACT.This article is freely available via Open Access. Click on the Publisher URL to access the full-text via the publisher's site

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival