EGS4 and MCNP4b MC Simulation of a Siemens KD2 Accelerator in 6 MV Photon Mode

The geometry of a Siemens Mevatron KD2 linear accelerator in 6 MV photon mode was modeled with EGS4 and MCNP4b. Energy spectra and other phase space distributions have been extensively compared in different plans along the beam line. The differences found have been evaluated both qualitative and quantitatively. The final aim was that both codes, running in different operating systems and with a common set of simulation conditions, met the requirement of fitting the experimental depth dose curves and dose profiles, measured in water for different field sizes. Whereas depth dose calculations are in a certain extent insensible to some simulation parameters like electron nominal energy, dose profiles have revealed to be a much better indicator to appreciate that feature. Fine energy tuning has been tried and the best fit was obtained for a nominal electron energy of 6.15 MeV

An Overview of Lipid Droplets in Cancer and Cancer Stem Cells

For decades, lipid droplets have been considered as the main cellular organelles involved in the fat storage, because of their lipid composition. However, in recent years, some new and totally unexpected roles have been discovered for them: (i) they are active sites for synthesis and storage of inflammatory mediators, and (ii) they are key players in cancer cells and tissues, especially in cancer stem cells. In this review, we summarize the main concepts related to the lipid droplet structure and function and their involvement in inflammatory and cancer processes

ROS and Lipid Droplet accumulation induced by high glucose exposure in healthy colon and Colorectal Cancer Stem Cells

Lipid Droplets (LDs) are emerging as crucial players in colon cancer development and maintenance. Their expression has been associated with high tumorigenicity in Cancer Stem Cells (CSCs), so that they have been proposed as a new functional marker in Colorectal Cancer Stem Cells (CR-CSCs). They are also indirectly involved in the modulation of the tumor microenvironment through the production of pro-inflammatory molecules. There is growing evidence that a possible connection between metabolic alterations and malignant transformation exists, although the effects of nutrients, primarily glucose, on the CSC behavior are still mostly unexplored. Glucose is an essential fuel for cancer cells, and the connections with LDs in the healthy and CSC populations merit to be more deeply investigated. Here, we showed that a high glucose concentration activated the PI3K/AKT pathway and increased the expression of CD133 and CD44v6 CSC markers. Additionally, glucose was responsible for the increased amount of Reactive Oxygen Species (ROS) and LDs in both healthy and CR-CSC samples. We also investigated the gene modulations following the HG treatment and found out that the healthy cell gene profile was the most affected. Lastly, Atorvastatin, a lipid-lowering drug, induced the highest mortality on CR-CSCs without affecting the healthy counterpart

Identification and quantification of organic aerosol from cooking and other sources in Barcelona using aerosol mass spectrometer data

PM<sub>1</sub> (particulate matter with an aerodynamic diameter <1 μm) non-refractory components and black carbon were measured continuously together with additional air quality and atmospheric parameters at an urban background site in Barcelona, Spain, during March 2009 (campaign DAURE, Determination of the sources of atmospheric Aerosols in Urban and Rural Environments in the western Mediterranean). Positive matrix factorization (PMF) was conducted on the organic aerosol (OA) data matrix measured by an aerosol mass spectrometer, on both unit mass (UMR) and high resolution (HR) data. Five factors or sources could be identified: LV-OOA (low-volatility oxygenated OA), related to regional, aged secondary OA; SV-OOA (semi-volatile oxygenated OA), a fresher oxygenated OA; HOA (hydrocarbon-like OA, related to traffic emissions); BBOA (biomass burning OA) from domestic heating or agricultural biomass burning activities; and COA (cooking OA). LV-OOA contributed 28% to OA, SV-OOA 27%, COA 17%, HOA 16%, and BBOA 11%. The COA HR spectrum contained substantial signal from oxygenated ions (O:C: 0.21) whereas the HR HOA spectrum had almost exclusively contributions from chemically reduced ions (O:C: 0.03). If we assume that the carbon in HOA is fossil while that in COA and BBOA is modern, primary OA in Barcelona contains a surprisingly high fraction (59%) of non-fossil carbon. <br></br> This paper presents a method for estimating cooking organic aerosol in ambient datasets based on the fractions of organic mass fragments at <i>m/z</i> 55 and 57: their data points fall into a V-shape in a scatter plot, with strongly influenced HOA data aligned to the right arm and strongly influenced COA data points aligned to the left arm. HR data show that this differentiation is mainly driven by the oxygen-containing ions C<sub>3</sub>H<sub>3</sub>O<sup>+</sup> and C<sub>3</sub>H<sub>5</sub>O<sup>+</sup>, even though their contributions to <i>m/z</i> 55 and 57 are low compared to the reduced ions C<sub>4</sub>H<sub>7</sub><sup>+</sup> and C<sub>4</sub>H<sub>9</sub><sup>+</sup>. A simple estimation method based on the markers <i>m/z</i> 55, 57, and 44 is developed here and allows for a first-order-estimation of COA in urban air. This study emphasizes the importance of cooking activities for ambient air quality and confirms the importance of chemical composition measurements with a high mass and time resolution

Wastewater nutrient removal in a mixed microalgae bacteria culture: effect of light and temperature on the microalgae bacteria competition

[EN] The aim of this study was to evaluate the effect of light intensity and temperature on nutrient removal and biomass productivity in a microalgae¿bacteria culture and their effects on the microalgae¿bacteria competition. Three experiments were carried out at constant temperature and various light intensities: 40, 85 and 125¿µE¿m¿2¿s¿1. Other two experiments were carried out at variable temperatures: 23¿±¿2°C and 28¿±¿2°C at light intensity of 85 and 125¿µE¿m¿2¿s¿1, respectively. The photobioreactor was fed by the effluent from an anaerobic membrane bioreactor. High nitrogen and phosphorus removal efficiencies (about 99%) were achieved under the following operating conditions: 85¿125¿µE¿m¿2¿s¿1 and 22¿±¿1°C. In the microalgae¿bacteria culture studied, increasing light intensity favoured microalgae growth and limited the nitrification process. However, a non-graduated temperature increase (up to 32°C) under the light intensities studied caused the proliferation of nitrifying bacteria and the nitrite and nitrate accumulation. Hence, light intensity and temperature are key parameters in the control of the microalgae¿bacteria competition. Biomass productivity significantly increased with light intensity, reaching 50.5¿±¿9.6, 80.3¿±¿6.5 and 94.3¿±¿7.9¿mgVSS¿L¿1¿d¿1 for a light intensity of 40, 85 and 125¿µE¿m¿2¿s¿1, respectivelyThis research work was possible because of Projects CTM2011-28595-C02-01 and CTM2011-28595-C02-02 [funded by the Spanish Ministry of Economy and Competitiveness jointly with the European Regional Development Fund and the Generalitat Valenciana GVA-ACOMP2013/203]. This research was also supported by the Spanish Ministry of Education, Culture and Sport via a pre doctoral FPU fellowship to the first author [FPU14/05082].Gonzalez-Camejo, J.; Barat, R.; Pachés Giner, MAV.; Murgui Mezquita, M.; Seco Torrecillas, A.; Ferrer, J. (2018). Wastewater nutrient removal in a mixed microalgae bacteria culture: effect of light and temperature on the microalgae bacteria competition. Environmental Technology. 39(4):503-515. https://doi.org/10.1080/09593330.2017.1305001S503515394Giménez, J. B., Robles, A., Carretero, L., Durán, F., Ruano, M. V., Gatti, M. N., … Seco, A. (2011). Experimental study of the anaerobic urban wastewater treatment in a submerged hollow-fibre membrane bioreactor at pilot scale. Bioresource Technology, 102(19), 8799-8806. doi:10.1016/j.biortech.2011.07.014Huang, Z., Ong, S. L., & Ng, H. Y. (2011). Submerged anaerobic membrane bioreactor for low-strength wastewater treatment: Effect of HRT and SRT on treatment performance and membrane fouling. Water Research, 45(2), 705-713. doi:10.1016/j.watres.2010.08.035Ruiz-Martinez, A., Martin Garcia, N., Romero, I., Seco, A., & Ferrer, J. (2012). Microalgae cultivation in wastewater: Nutrient removal from anaerobic membrane bioreactor effluent. Bioresource Technology, 126, 247-253. doi:10.1016/j.biortech.2012.09.022Chisti, Y. (2007). Biodiesel from microalgae. Biotechnology Advances, 25(3), 294-306. doi:10.1016/j.biotechadv.2007.02.001Rawat, I., Bhola, V., Kumar, R. R., & Bux, F. (2013). Improving the feasibility of producing biofuels from microalgae using wastewater. Environmental Technology, 34(13-14), 1765-1775. doi:10.1080/09593330.2013.826287Collet, P., Hélias, A., Lardon, L., Ras, M., Goy, R.-A., & Steyer, J.-P. (2011). Life-cycle assessment of microalgae culture coupled to biogas production. Bioresource Technology, 102(1), 207-214. doi:10.1016/j.biortech.2010.06.154Milledge, J. J. (2010). Commercial application of microalgae other than as biofuels: a brief review. Reviews in Environmental Science and Bio/Technology, 10(1), 31-41. doi:10.1007/s11157-010-9214-7Posadas, E., García-Encina, P.-A., Soltau, A., Domínguez, A., Díaz, I., & Muñoz, R. (2013). Carbon and nutrient removal from centrates and domestic wastewater using algal–bacterial biofilm bioreactors. Bioresource Technology, 139, 50-58. doi:10.1016/j.biortech.2013.04.008Podevin, M., De Francisci, D., Holdt, S. L., & Angelidaki, I. (2014). Effect of nitrogen source and acclimatization on specific growth rates of microalgae determined by a high-throughput in vivo microplate autofluorescence method. Journal of Applied Phycology, 27(4), 1415-1423. doi:10.1007/s10811-014-0468-2Meseck, S. L., Smith, B. C., Wikfors, G. H., Alix, J. H., & Kapareiko, D. (2006). Nutrient interactions between phytoplankton and bacterioplankton under different carbon dioxide regimes. Journal of Applied Phycology, 19(3), 229-237. doi:10.1007/s10811-006-9128-5Risgaard-Petersen, N., Nicolaisen, M. H., Revsbech, N. P., & Lomstein, B. A. (2004). Competition between Ammonia-Oxidizing Bacteria and Benthic Microalgae. Applied and Environmental Microbiology, 70(9), 5528-5537. doi:10.1128/aem.70.9.5528-5537.2004Tiquia-Arashiro, S. M., & Mormile, M. (2013). Sustainable technologies: bioenergy and biofuel from biowaste and biomass. Environmental Technology, 34(13-14), 1637-1638. doi:10.1080/09593330.2013.834162Jordan, B. R. (1996). The Effects of Ultraviolet-B Radiation on Plants: A Molecular Perspective. Advances in Botanical Research, 97-162. doi:10.1016/s0065-2296(08)60057-9Znad, H., Naderi, G., Ang, H. M., & Tade, M. O. (2012). CO2 Biomitigation and Biofuel Production Using Microalgae: Photobioreactors Developments and Future Directions. Advances in Chemical Engineering. doi:10.5772/32568Martínez, M. (2000). Nitrogen and phosphorus removal from urban wastewater by the microalga Scenedesmus obliquus. Bioresource Technology, 73(3), 263-272. doi:10.1016/s0960-8524(99)00121-2Xin, L., Hong-ying, H., & Yu-ping, Z. (2011). Growth and lipid accumulation properties of a freshwater microalga Scenedesmus sp. under different cultivation temperature. Bioresource Technology, 102(3), 3098-3102. doi:10.1016/j.biortech.2010.10.055Robles, Á., Durán, F., Ruano, M. V., Ribes, J., Rosado, A., Seco, A., & Ferrer, J. (2015). Instrumentation, control, and automation for submerged anaerobic membrane bioreactors. Environmental Technology, 36(14), 1795-1806. doi:10.1080/09593330.2015.1012180Reynolds, C. S. (2006). The Ecology of Phytoplankton. doi:10.1017/cbo9780511542145Küster, E., Dorusch, F., & Altenburger, R. (2005). EFFECTS OF HYDROGEN SULFIDE TO VIBRIO FISCHERI, SCENEDESMUS VACUOLATUS, AND DAPHNIA MAGNA. Environmental Toxicology and Chemistry, 24(10), 2621. doi:10.1897/04-546r.1Park, J., Jin, H.-F., Lim, B.-R., Park, K.-Y., & Lee, K. (2010). Ammonia removal from anaerobic digestion effluent of livestock waste using green alga Scenedesmus sp. Bioresource Technology, 101(22), 8649-8657. doi:10.1016/j.biortech.2010.06.142McGinn, P. J., Dickinson, K. E., Park, K. C., Whitney, C. G., MacQuarrie, S. P., Black, F. J., … O’Leary, S. J. B. (2012). Assessment of the bioenergy and bioremediation potentials of the microalga Scenedesmus sp. AMDD cultivated in municipal wastewater effluent in batch and continuous mode. Algal Research, 1(2), 155-165. doi:10.1016/j.algal.2012.05.001Mara, D. D., & Feachem, R. G. A. (2003). Unitary environmental classification of water- and excreta-related communicable diseases. Handbook of Water and Wastewater Microbiology, 185-192. doi:10.1016/b978-012470100-7/50012-1Jeffrey, S. W., & Humphrey, G. F. (1975). New spectrophotometric equations for determining chlorophylls a, b, c1 and c2 in higher plants, algae and natural phytoplankton. Biochemie und Physiologie der Pflanzen, 167(2), 191-194. doi:10.1016/s0015-3796(17)30778-3Laliberté, G., Lessard, P., de la Noüe, J., & Sylvestre, S. (1997). Effect of phosphorus addition on nutrient removal from wastewater with the cyanobacterium Phormidium bohneri. Bioresource Technology, 59(2-3), 227-233. doi:10.1016/s0960-8524(96)00144-7Pachés, M., Romero, I., Hermosilla, Z., & Martinez-Guijarro, R. (2012). PHYMED: An ecological classification system for the Water Framework Directive based on phytoplankton community composition. Ecological Indicators, 19, 15-23. doi:10.1016/j.ecolind.2011.07.003Xin, L., Hong-ying, H., Ke, G., & Jia, Y. (2010). Growth and nutrient removal properties of a freshwater microalga Scenedesmus sp. LX1 under different kinds of nitrogen sources. Ecological Engineering, 36(4), 379-381. doi:10.1016/j.ecoleng.2009.11.003Wang, L., Min, M., Li, Y., Chen, P., Chen, Y., Liu, Y., … Ruan, R. (2009). Cultivation of Green Algae Chlorella sp. in Different Wastewaters from Municipal Wastewater Treatment Plant. Applied Biochemistry and Biotechnology, 162(4), 1174-1186. doi:10.1007/s12010-009-8866-7Pancha, I., Chokshi, K., George, B., Ghosh, T., Paliwal, C., Maurya, R., & Mishra, S. (2014). Nitrogen stress triggered biochemical and morphological changes in the microalgae Scenedesmus sp. CCNM 1077. Bioresource Technology, 156, 146-154. doi:10.1016/j.biortech.2014.01.025Sarat Chandra, T., Deepak, R. S., Maneesh Kumar, M., Mukherji, S., Chauhan, V. S., Sarada, R., & Mudliar, S. N. (2016). Evaluation of indigenous fresh water microalga Scenedesmus obtusus for feed and fuel applications: Effect of carbon dioxide, light and nutrient sources on growth and biochemical characteristics. Bioresource Technology, 207, 430-439. doi:10.1016/j.biortech.2016.01.044Krustok, I., Odlare, M., Truu, J., & Nehrenheim, E. (2016). Inhibition of nitrification in municipal wastewater-treating photobioreactors: Effect on algal growth and nutrient uptake. Bioresource Technology, 202, 238-243. doi:10.1016/j.biortech.2015.12.020Chen, X., Goh, Q. Y., Tan, W., Hossain, I., Chen, W. N., & Lau, R. (2011). Lumostatic strategy for microalgae cultivation utilizing image analysis and chlorophyll a content as design parameters. Bioresource Technology, 102(10), 6005-6012. doi:10.1016/j.biortech.2011.02.061Powell, N., Shilton, A., Chisti, Y., & Pratt, S. (2009). Towards a luxury uptake process via microalgae – Defining the polyphosphate dynamics. Water Research, 43(17), 4207-4213. doi:10.1016/j.watres.2009.06.011Cabello, J., Toledo-Cervantes, A., Sánchez, L., Revah, S., & Morales, M. (2015). Effect of the temperature, pH and irradiance on the photosynthetic activity by Scenedesmus obtusiusculus under nitrogen replete and deplete conditions. Bioresource Technology, 181, 128-135. doi:10.1016/j.biortech.2015.01.034Zhu, W., Wan, L., & Zhao, L. (2010). Effect of nutrient level on phytoplankton community structure in different water bodies. Journal of Environmental Sciences, 22(1), 32-39. doi:10.1016/s1001-0742(09)60071-1Daims, H., Brühl, A., Amann, R., Schleifer, K.-H., & Wagner, M. (1999). The Domain-specific Probe EUB338 is Insufficient for the Detection of all Bacteria: Development and Evaluation of a more Comprehensive Probe Set. Systematic and Applied Microbiology, 22(3), 434-444. doi:10.1016/s0723-2020(99)80053-8Daims, H., Nielsen, J. L., Nielsen, P. H., Schleifer, K.-H., & Wagner, M. (2001). In Situ Characterization of Nitrospira-Like Nitrite-Oxidizing Bacteria Active in Wastewater Treatment Plants. Applied and Environmental Microbiology, 67(11), 5273-5284. doi:10.1128/aem.67.11.5273-5284.2001analysis of nitrifying bacteria in sewage treatment plants. (1996). Water Science and Technology, 34(1-2). doi:10.1016/0273-1223(96)00514-

Measurement of the ratio of branching fractions BR(B0 -> K*0 gamma)/BR(Bs0 -> phi gamma)

The ratio of branching fractions of the radiative B decays B0 -> K*0 gamma and Bs0 -> phi gamma has been measured using 0.37 fb-1 of pp collisions at a centre of mass energy of sqrt(s) = 7 TeV, collected by the LHCb experiment. The value obtained is BR(B0 -> K*0 gamma)/BR(Bs0 -> phi gamma) = 1.12 +/- 0.08 ^{+0.06}_{-0.04} ^{+0.09}_{-0.08}, where the first uncertainty is statistical, the second systematic and the third is associated to the ratio of fragmentation fractions fs/fd. Using the world average for BR(B0 -> K*0 gamma) = (4.33 +/- 0.15) x 10^{-5}, the branching fraction BR(Bs0 -> phi gamma) is measured to be (3.9 +/- 0.5) x 10^{-5}, which is the most precise measurement to date.Comment: 15 pages, 1 figure, 2 table

Measurement of the CKM angle γ from a combination of B±→Dh± analyses

A combination of three LHCb measurements of the CKM angle γ is presented. The decays B±→D K± and B±→Dπ± are used, where D denotes an admixture of D0 and D0 mesons, decaying into K+K−, π+π−, K±π∓, K±π∓π±π∓, K0Sπ+π−, or K0S K+K− final states. All measurements use a dataset corresponding to 1.0 fb−1 of integrated luminosity. Combining results from B±→D K± decays alone a best-fit value of γ =72.0◦ is found, and confidence intervals are set γ ∈ [56.4,86.7]◦ at 68% CL, γ ∈ [42.6,99.6]◦ at 95% CL. The best-fit value of γ found from a combination of results from B±→Dπ± decays alone, is γ =18.9◦, and the confidence intervals γ ∈ [7.4,99.2]◦ ∪ [167.9,176.4]◦ at 68% CL are set, without constraint at 95% CL. The combination of results from B± → D K± and B± → Dπ± decays gives a best-fit value of γ =72.6◦ and the confidence intervals γ ∈ [55.4,82.3]◦ at 68% CL, γ ∈ [40.2,92.7]◦ at 95% CL are set. All values are expressed modulo 180◦, and are obtained taking into account the effect of D0–D0 mixing

Search for CP violation in D+→K−K+π+D^{+} \to K^{-}K^{+}\pi^{+} decays

A model-independent search for direct CP violation in the Cabibbo suppressed decay $D^+ \to K^- K^+\pi^+$ in a sample of approximately 370,000 decays is carried out. The data were collected by the LHCb experiment in 2010 and correspond to an integrated luminosity of 35 pb$^{-1}$. The normalized Dalitz plot distributions for $D^+$ and $D^-$ are compared using four different binning schemes that are sensitive to different manifestations of CP violation. No evidence for CP asymmetry is found.Comment: 13 pages, 8 figures, submitted to Phys. Rev.

Differential branching fraction and angular analysis of the decay B0→K∗0μ+μ−

The angular distribution and differential branching fraction of the decay B 0→ K ∗0 μ + μ − are studied using a data sample, collected by the LHCb experiment in pp collisions at s√=7 TeV, corresponding to an integrated luminosity of 1.0 fb−1. Several angular observables are measured in bins of the dimuon invariant mass squared, q 2. A first measurement of the zero-crossing point of the forward-backward asymmetry of the dimuon system is also presented. The zero-crossing point is measured to be q20=4.9±0.9GeV2/c4 , where the uncertainty is the sum of statistical and systematic uncertainties. The results are consistent with the Standard Model predictions

Longitudinal development of antibody responses in COVID-19 patients of different severity with ELISA, peptide, and glycan arrays : an immunological case series

The current COVID-19 pandemic is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). A better understanding of its immunogenicity can be important for the development of improved diagnostics, therapeutics, and vaccines. Here, we report the longitudinal analysis of three COVID-19 patients with moderate (1) and mild disease (2 and 3). Antibody serum responses were analyzed using spike glycoprotein enzyme linked immunosorbent assay (ELISA), full-proteome peptide, and glycan microarrays. ELISA immunoglobulin A, G, and M (IgA, IgG, and IgM) signals increased over time for individuals 1 and 2, whereas 3 only showed no clear positive IgG and IgM result. In contrast, peptide microarrays showed increasing IgA/G signal intensity and epitope spread only in the moderate patient 1 over time, whereas early but transient IgA and stable IgG responses were observed in the two mild cases 2 and 3. Glycan arrays showed an interaction of antibodies to fragments of high-mannose and core N-glycans, present on the viral shield. In contrast to protein ELISA, microarrays allow for a deeper understanding of IgA, IgG, and IgM antibody responses to specific epitopes of the whole proteome and glycans of SARS-CoV-2 in parallel. In the future, this may help to better understand and to monitor vaccination programs and monoclonal antibodies as therapeutics