Cordyceps spp.: A Review on Its Immune-Stimulatory and Other Biological Potentials

In recent decades, interest in the Cordyceps genus has amplified due to its immunostimulatory potential. Cordyceps species, its extracts, and bioactive constituents have been related with cytokine production such as interleukin (IL)-1ß, IL-2, IL-6, IL-8, IL-10, IL-12, and tumor necrosis factor (TNF)-a, phagocytosis stimulation of immune cells, nitric oxide production by increasing inducible nitric oxide synthase activity, and stimulation of inflammatory response via mitogen-activated protein kinase pathway. Other pharmacological activities like antioxidant, anti-cancer, antihyperlipidemic, anti-diabetic, anti-fatigue, anti-aging, hypocholesterolemic, hypotensive, vasorelaxation, anti-depressant, aphrodisiac, and kidney protection, has been reported in pre-clinical studies. These biological activities are correlated with the bioactive compounds present in Cordyceps including nucleosides, sterols, flavonoids, cyclic peptides, phenolic, bioxanthracenes, polyketides, and alkaloids, being the cyclic peptides compounds the most studied. An organized review of the existing literature was executed by surveying several databanks like PubMed, Scopus, etc. using keywords like Cordyceps, cordycepin, immune system, immunostimulation, immunomodulatory, pharmacology, anti-cancer, anti-viral, clinical trials, ethnomedicine, pharmacology, phytochemical analysis, and different species names. This review collects and analyzes state-of-the-art about the properties of Cordyceps species along with ethnopharmacological properties, application in food, chemical compounds, extraction of bioactive compounds, and various pharmacological properties with a special focus on the stimulatory properties of immunity.This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1G1A1004667), Republic of Korea

Genetic variation among species, races, forms and inbred lines of lac insects belonging to the genus Kerria (Homoptera, Tachardiidae)

The lac insects (Homoptera: Tachardiidae), belonging to the genus Kerria, are commercially exploited for the production of lac. Kerria lacca is the most commonly used species in India. RAPD markers were used for assessing genetic variation in forty-eight lines of Kerria, especially among geographic races, infrasubspecific forms, cultivated lines, inbred lines, etc., of K. lacca. In the 48 lines studied, the 26 RAPD primers generated 173 loci, showing 97.7% polymorphism. By using neighbor-joining, the dendrogram generated from the similarity matrix resolved the lines into basically two clusters and outgroups. The major cluster, comprising 32 lines, included mainly cultivated lines of the rangeeni form, geographic races and inbred lines of K. lacca. The second cluster consisted of eight lines of K. lacca, seven of the kusmi form and one of the rangeeni from the southern state of Karnataka. The remaining eight lines formed a series of outgroups, this including a group of three yellow mutant lines of K. lacca and other species of the Kerria studied, among others. Color mutants always showed distinctive banding patterns compared to their wild-type counterparts from the same population. This study also adds support to the current status of kusmi and rangeeni, as infraspecific forms of K. lacca

Integrated methodological framework fos assesing the risk of failure in water supply incorporating drought forecast. Case study: Andean regulated river basin

[EN] Hydroclimatic drought conditions can affect the hydrological services offered by mountain river basins causing severe impacts on the population, becoming a challenge for water resource managers in Andean river basins. This study proposes an integrated methodological framework for assessing the risk of failure in water supply, incorporating probabilistic drought forecasts, which assists in making decisions regarding the satisfaction of consumptive, non-consumptive and environmental requirements under water scarcity conditions. Monte Carlo simulation was used to assess the risk of failure in multiple stochastic scenarios, which incorporate probabilistic forecasts of drought events based on a Markov chains (MC) model using a recently developed drought index (DI). This methodology was tested in the Machángara river basin located in the south of Ecuador. Results were grouped in integrated satisfaction indexes of the system (DSIG). They demonstrated that the incorporation of probabilistic drought forecasts could better target the projections of simulation scenarios, with a view of obtaining realistic situations instead of optimistic projections that would lead to riskier decisions. Moreover, they contribute to more effective results in order to propose multiple alternatives for prevention and/or mitigation under drought conditions.This study was part of the doctoral thesis of Aviles A. at the Technical University of Valencia. This research was funded by the University of Cuenca through its Research Department (DIUC) and the Municipal public enterprise of telecommunications, drinking water, sewage and sanitation of Cuenca (ETAPA) through the projects: BIdentificacion de los procesos hidrometeorologicos que desencadenan inundaciones en la ciudad de Cuenca usando un radar de precipitacion" and "Ciclos meteorologicos y evapotranspiracion a lo largo de una gradiente altitudinal del Parque Nacional Cajas". The authors also thank INAMHI and the CBRM for providing the information for this study. The authors wish to thank the Spanish Ministry of Economy and Competitiveness for its financial support through the ERAS project (CTM2016-77804-P). We thank Angel Vazquez, who helped in the programming of the multiple simulations. Also we thank to the TropiSeca project.Avilés-Añazco, A.; Solera Solera, A.; Paredes Arquiola, J.; Pedro Monzonís, M. (2018). Integrated methodological framework fos assesing the risk of failure in water supply incorporating drought forecast. Case study: Andean regulated river basin. Water Resources Management. 32(4):1209-1223. https://doi.org/10.1007/s11269-017-1863-7S12091223324Andreu J, Capilla J, Sanchís E (1996) AQUATOOL, a generalized decision-support system for water-resources planning and operational management. J Hydrol 177(3-4):269–291. https://doi.org/10.1016/0022-1694(95)02963-XAndreu J, Solera A, Capilla J, Ferrer J (2007) Modelo SIMGES para simulación de cuencas. Manual de usuario v3. 00. Universidad Politécnica de Valencia, ValenciaAndreu J, Ferrer J, Perez MA et al (2013) Drought planning and management in the Júcar River Basin, Spain. In: Schwabe K et al (eds) Drought in arid and semi-arid regions. Springer science, Dordrecht, pp 237–249. https://doi.org/10.1007/978-94-007-6636-5_13Avilés A, Solera A (2013) Análisis de sistemas de recursos hídricos de la cuenca del rio Tomebamba en Ecuador, mediante modelos estocásticos y de gestión. In: Solera A, Paredes J, Andreu J (eds) Aplicaciones de sistemas soporte a la decisión en planificación y gestión integradas de cuencas hidrográficas. Marcombo, Barcelona, España pp 51–61Avilés A, Célleri R, Paredes J, Solera A (2015) Evaluation of Markov chain based drought forecasts in an Andean Regulated River basin using the skill scores RPS and GMSS. Water Resour Manag 29(6):1949–1963. https://doi.org/10.1007/s11269-015-0921-2Avilés A, Célleri R, Solera A, Paredes J (2016) Probabilistic forecasting of drought events using Markov chain-and Bayesian network-based models: a case study of an Andean Regulated River Basin. Water 8:1–16Barua S, Ng A, Perera B (2012) Drought assessment and forecasting: a case study on the Yarra River catchment in Victoria, Australia. Aust J Water Resour 15(2):95–108. https://doi.org/10.7158/W10-848.2012.15.2Bazaraa MS, Jarvis JJ, Sherali HD (2011) Linear programming and network flows, fourth Edi. John Wiley & Sons, New JerseyBrown C, Baroang KM, Conrad E et al (2010) IRI technical report 10–15, managing climate risk in water supply systems. Palisades, NYCancelliere A, Di Mauro G, Bonaccorso B, Rossi G (2007) Drought forecasting using the standardized precipitation index. Water Resour Manag 21(5):801–819. https://doi.org/10.1007/s11269-006-9062-yCancelliere A, Nicolosi V, Rossi G (2009) Assessment of drought risk in water supply systems in coping with drought risk in agriculture and water supply systems. Advances in natural and technological hazards research 26. In: Coping with drought risk in agriculture. Springer, pp 93–109. https://doi.org/10.1007/978-1-4020-9045-5_8Chen YD, Zhang Q, Xiao M, Singh VP, Zhang S (2016) Probabilistic forecasting of seasonal droughts in the Pearl River basin, China. Stoch Environ Res Risk Assess 30(7):2031–2040. https://doi.org/10.1007/s00477-015-1174-6Gong G, Wang L, Condon L, Shearman A, Lall U (2010) A simple framework for incorporating seasonal Streamflow forecasts into existing water resource management practices. JAWRA J Am Water Resour Assoc 46(3):574–585. https://doi.org/10.1111/j.1752-1688.2010.00435.xHaro D, Solera A, Paredes J, Andreu J (2014) Methodology for drought risk assessment in within-year regulated reservoir systems. Application to the Orbigo River system (Spain). Water Resour Manag 28(11):3801–3814. https://doi.org/10.1007/s11269-014-0710-3Haro-Monteagudo D, Solera A, Andreu J (2017) Drought early warning based on optimal risk forecasts in regulated river systems: application to the Jucar River basin (Spain). J Hydrol 544:36–45. https://doi.org/10.1016/j.jhydrol.2016.11.022Hashimoto T, Loucks DP, Stedinger JR (1982) Reliability, resiliency, and vulnerability criteria. Water Resour Res 18(1):14–20. https://doi.org/10.1029/WR018i001p00014Hwang Y, Carbone GJ (2009) Ensemble forecasts of drought indices using a conditional residual resampling technique. J Appl Meteorol Climatol 48(7):1289–1301. https://doi.org/10.1175/2009JAMC2071.1Kao S-C, Govindaraju RS (2010) A copula-based joint deficit index for droughts. J Hydrol 380(1-2):121–134. https://doi.org/10.1016/j.jhydrol.2009.10.029Keyantash JA, Dracup JA (2004) An aggregate drought index: assessing drought severity based on fluctuations in the hydrologic cycle and surface water storage. Water Resour Res 40(9):1–13. https://doi.org/10.1029/2003WR002610Khadr M (2016) Forecasting of meteorological drought using hidden Markov model (case study: the upper Blue Nile river basin, Ethiopia). Ain Shams Eng J 7(1):47–56. https://doi.org/10.1016/j.asej.2015.11.005Madadgar S, Moradkhani H (2013) A Bayesian framework for probabilistic seasonal drought forecasting. J Hydrometeorol 14(6):1685–1706. https://doi.org/10.1175/JHM-D-13-010.1Madadgar S, Moradkhani H (2014) Spatio-temporal drought forecasting within Bayesian networks. J Hydrol 512:134–146. https://doi.org/10.1016/j.jhydrol.2014.02.039Mahmoudzadeh H, Mahmoudzadeh H, Afshar M, Yousefi S (2016) Applying first-order Markov chains and SPI drought index to monitor and forecast drought in West Azerbaijan Province of Iran. Int J Geo Sci Environ Plan 1:44–53. 10.22034/ijgsep.2016.40669Mishra AK, Singh VP (2010) Review paper a review of drought concepts. J Hydrol 391(1-2):202–216. https://doi.org/10.1016/j.jhydrol.2010.07.012Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resour Manag 23(5):881–897. https://doi.org/10.1007/s11269-008-9305-1Ochola WO, Kerkides P (2003) A Markov chain simulation model for predicting critical wet and dry spells in Kenya: Analysing rainfall events in the kano plains. Irrig Drain 52(4):327–342. https://doi.org/10.1002/ird.094Paulo AA, Pereira LS (2007) Prediction of SPI drought class transitions using Markov chains. Water Resour Manag 21(10):1813–1827. https://doi.org/10.1007/s11269-006-9129-9Phan TD, Smart JCR, Capon SJ, Hadwen WL, Sahin O (2016) Applications of Bayesian belief networks in water resource management: a systematic review. Environ Model Softw 85:98–111. https://doi.org/10.1016/j.envsoft.2016.08.006Pouget L, Roldán T, Gómez M et al (2015) Use of seasonal climate predictions in the water sector—preliminary results from the EUPORIAS project. In: Andreu J, Solera A, Paredes J et al (eds) Drought: research and science-policy interfacing. Taylor & Francis Group, London, UK, p 247Rossi G, Cancelliere A (2013) Managing drought risk in water supply systems in Europe: a review. Int J Water Resour Dev 29(2):272–289. https://doi.org/10.1080/07900627.2012.713848Rossi G, Caporali E, Garrote L (2012) Definition of risk indicators for reservoirs management optimization. Water Resour Manag 26(4):981–996. https://doi.org/10.1007/s11269-011-9842-xSánchez S, Andreu J, Solera A (2001) Gestión de Recursos Hídricos con Decisiones Basadas en Estimación del Riesgo. Universidad Politécnica De Valencia, ValenciaSandoval-Solis S, McKinney DC, Loucks M (2011) Sustainability index for water resources planning and management. J Water Resour Plan Manag 137(5):381–390. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000134Sankarasubramanian A, Lall U, Devineni N, Espinueva S (2009) The role of monthly updated climate forecasts in improving intraseasonal water allocation. J Appl Meteorol Climatol 48(7):1464–1482. https://doi.org/10.1175/2009JAMC2122.1Shukla S, Wood AW (2008) Use of a standardized runoff index for characterizing hydrologic drought. Geophys Res Lett 35(2):1–7. https://doi.org/10.1029/2007GL032487Staudinger M, Stahl K, Seibert J (2014) A drought index accounting for snow. Water Resour Res 50(10):7861–7872. https://doi.org/10.1002/2013WR015143Sveinsson O, Salas JD, Lane W, Frevert D (2007) Stochastic analysis, modeling, and simulation (SAMS) version 2007, user’s manual. Computing Hydrology Laboratory, Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, ColoradoSvoboda M, Hayes M, Wilhite D, Tadesse T (2004) Recent advances in drought monitoring. Drought Mitig Cent Fac Publ 6:6Vogel RM (2017) Stochastic watershed models for hydrologic risk management. Water Secur 1:28–35. https://doi.org/10.1016/j.wasec.2017.06.001Wilks DS (2011) Statistical methods in the atmospheric sciences, third edit. Academic Press, USAWorld Meteorological Organization (2012) Standardized precipitation index user Guide (M. Svoboda, M. Hayes and D. Wood). (WMO - No. 1090), Geneva

Measurement of the Forward-Backward Asymmetry in the B -> K(*) mu+ mu- Decay and First Observation of the Bs -> phi mu+ mu- Decay

We reconstruct the rare decays $B^+ \to K^+\mu^+\mu^-$, $B^0 \to K^{*}(892)^0\mu^+\mu^-$, and $B^0_s \to \phi(1020)\mu^+\mu^-$ in a data sample corresponding to $4.4 {\rm fb^{-1}}$ collected in $p\bar{p}$ collisions at $\sqrt{s}=1.96 {\rm TeV}$ by the CDF II detector at the Fermilab Tevatron Collider. Using $121 \pm 16$ $B^+ \to K^+\mu^+\mu^-$ and $101 \pm 12$ $B^0 \to K^{*0}\mu^+\mu^-$ decays we report the branching ratios. In addition, we report the measurement of the differential branching ratio and the muon forward-backward asymmetry in the $B^+$ and $B^0$ decay modes, and the $K^{*0}$ longitudinal polarization in the $B^0$ decay mode with respect to the squared dimuon mass. These are consistent with the theoretical prediction from the standard model, and most recent determinations from other experiments and of comparable accuracy. We also report the first observation of the $B^0_s \to \phi\mu^+\mu^- decay and measure its branching ratio${\mathcal{B}}(B^0_s \to \phi\mu^+\mu^-) = [1.44 \pm 0.33 \pm 0.46] \times 10^{-6}$using$27 \pm 6$signal events. This is currently the most rare$B^0_s$ decay observed.Comment: 7 pages, 2 figures, 3 tables. Submitted to Phys. Rev. Let

Measurements of the properties of Lambda_c(2595), Lambda_c(2625), Sigma_c(2455), and Sigma_c(2520) baryons

We report measurements of the resonance properties of Lambda_c(2595)+ and Lambda_c(2625)+ baryons in their decays to Lambda_c+ pi+ pi- as well as Sigma_c(2455)++,0 and Sigma_c(2520)++,0 baryons in their decays to Lambda_c+ pi+/- final states. These measurements are performed using data corresponding to 5.2/fb of integrated luminosity from ppbar collisions at sqrt(s) = 1.96 TeV, collected with the CDF II detector at the Fermilab Tevatron. Exploiting the largest available charmed baryon sample, we measure masses and decay widths with uncertainties comparable to the world averages for Sigma_c states, and significantly smaller uncertainties than the world averages for excited Lambda_c+ states.Comment: added one reference and one table, changed order of figures, 17 pages, 15 figure

Search for a New Heavy Gauge Boson Wprime with Electron + missing ET Event Signature in ppbar collisions at sqrt(s)=1.96 TeV

We present a search for a new heavy charged vector boson $W^\prime$ decaying to an electron-neutrino pair in $p\bar{p}$ collisions at a center-of-mass energy of 1.96\unit{TeV}. The data were collected with the CDF II detector and correspond to an integrated luminosity of 5.3\unit{fb}^{-1}. No significant excess above the standard model expectation is observed and we set upper limits on $\sigma\cdot{\cal B}(W^\prime\to e\nu)$. Assuming standard model couplings to fermions and the neutrino from the $W^\prime$ boson decay to be light, we exclude a $W^\prime$ boson with mass less than 1.12\unit{TeV/}c^2 at the 95\unit{%} confidence level.Comment: 7 pages, 2 figures Submitted to PR

Compressed representation of a partially defined integer function over multiple arguments

In OLAP (OnLine Analitical Processing) data are analysed in an n-dimensional cube. The cube may be represented as a partially defined function over n arguments. Considering that often the function is not defined everywhere, we ask: is there a known way of representing the function or the points in which it is defined, in a more compact manner than the trivial one

Assessing the Effects of Responsible Leadership and Ethical Conflict on Behavioral Intention

[[abstract]]This study develops a research model that elaborates how responsible leadership and ethical conflict influence employees from the perspectives of role theory and attachment theory. Its empirical results reveal that turnover intention indirectly relates to ethical conflict and responsible leadership via the mediating mechanisms of organizational identification and organizational uncertainty. At the same time, helping intention indirectly relates to ethical conflict and responsible leadership only through organizational identification. Finally, the managerial implications for international business and research limitations based on the empirical results are discussed.[[notice]]補正完