Author Correction: Global disease outbreaks associated with the 2015-2016 El Niño Event.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Global Disease Outbreaks Associated with the 2015-2016 El Niño Event.

Interannual climate variability patterns associated with the El Niño-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 2015-2016 El Niño event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Niño-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (14-81% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.5-28% higher during years with El Niño events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p < 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p < 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases.

Degradation of the cyanotoxin microcystin-LR using iron-based photocatalysts under visible light illumination.

In this study, a simple and low-cost method to synthesize iron(III) oxide nanopowders in large quantity was successfully developed for the photocatalytic degradation of microcystin-LR (MC-LR). Two visible light-active iron(III) oxide samples (MG-9 calcined at 200 °C for 5 h and MG-11 calcined at 180 °C for 16 h) with a particle size of 5-20 nm were prepared via thermal decomposition of ferrous oxalate dihydrate in air without any other modifications such as doping. The synthesized samples were characterized by X-ray powder diffraction, 57Fe Mössbauer spectroscopy, transmission electron microscopy, Brunauer-Emmett-Teller (BET) specific surface area analysis, and UV-visible diffuse reflectance spectroscopy. The samples exhibited similar phase composition (a mixture of α-Fe2O3 and γ-Fe2O3), particle size distribution (5-20 nm), particle morphology, and degree of agglomeration, but different specific surface areas (234 m2 g-1 for MG-9 and 207 m2 g-1 for MG-11). The results confirmed higher photocatalytic activity of the catalyst with higher specific surface area. The highest photocatalytic activity of the sample to decompose MC-LR was observed at solution pH of 3.0 and catalyst loading of 0.5 g L-1 due to large amount of MC-LR adsorption, but a little iron dissolution of 0.0065 wt% was observed. However, no iron leaching was observed at pH 5.8 even though the overall MC-LR removal was slightly lower than at pH 3.0. Thus, the pH 5.8 could be an appropriate operating condition for the catalyst to avoid problems of iron contamination by the catalyst. Moreover, magnetic behavior of γ-Fe2O3 gives a possibility for an easy separation of the catalyst particles after their use.

Remarkable efficiency of phosphate removal: Ferrate(VI)-induced in situ sorption on core-shell nanoparticles.

Despite the importance of phosphorus as a nutrient for humans and its role in ecological sustainability, its high abundance, resulting in large part from human activities, causes eutrophication that negatively affects the environment and public health. Here, we present the use of ferrate(VI) as an alternative agent for removing phosphorus from aqueous media. We address the mechanism of phosphate removal as a function of the Fe/P mass ratio and the pH value of the solution. The isoelectric point of γ-Fe2O3 nanoparticles, formed as dominant Fe(VI) decomposition products, was identified to play a crucial role in predicting their efficiency in removing of phosphates. Importantly, it was found that the removal efficiency dramatically changes if Fe(VI) is added before (ex-situ conditions) or after (in-situ conditions) the introduction of phosphates into water. Removal under in-situ conditions showed remarkable sorption capacity of 143.4 mg P per gram of ferric precipitates due to better accessibility of active surface sites on in-situ formed ferric oxides/oxyhydroxides. At pH = 6.0-7.0, complete removal of phosphates was observed at a relatively low Fe/P mass ratio (5:1). The results show that phosphates are removed from water solely by sorption on the surface of γ-Fe2O3/γ-FeOOH core/shell nanoparticles. The advantages of Fe(VI) utilization include its environmentally friendly nature, the possibility of easy separation of the final product from water by a magnetic field or by natural settling, and the capacity for successful phosphate elimination at pH values near the neutral range and at low Fe/P mass ratios.

Ferrates(FeVI, FeV, and FeIV) oxidation of iodide: Formation of triiodide.

The presence of iodide (I(-)) in water during disinfection and oxidative treatment of water is a potential health concern because of the formation of iodinated disinfection by-products (DBPs), which may be more toxic than chlorinated DBPs. The kinetics of the oxidation of I(-) by a greener oxidant, ferrate(VI) (Fe(VI)O4(2-), Fe(VI)) was determined as a function of pH. The second-order rate constants (k, M(-1) s(-1)) decreased from 3.9 × 10(4) M(-1) s(-1) at pH 5.0 to 1.2 × 10(1) M(-1) s(-1) at pH 10.3. The kinetics results could be described by the reactivity of monoprotonated species of Fe(VI) (HFe(VI)O4(-)) with I(-). In excess I(-) concentration, triiodide (I3(-)) was formed and the stoichiometry of ∼1:1 ([Fe(VI)]:[I3(-)]) was found in both acidic and basic pH. Ferrate(V) (Fe(V)O4(3-), Fe(V)) and ferrate(IV) (Fe(VI)O4(4-), Fe(IV)) also showed the formation of I3(-) in presence of excess I(-). A mechanism of the formation of I3(-) is proposed, which is consistent with the observed stoichiometry of 1:1. The oxidative treatment of I(-) in water will be rapid (t1/2 = 0.6 s at pH 7.0 using 10 mg L(-1) K2FeO4). The implications of the results and their comparison with the oxidation of I(-) by conventional disinfectants/oxidants in water treatment are briefly discussed.

Associations between seasonal influenza and meteorological parameters in Costa Rica, Honduras and Nicaragua.

Seasonal influenza affects a considerable proportion of the global population each year. We assessed the association between subnational influenza activity and temperature, specific humidity and rainfall in three Central America countries, i.e. Costa Rica, Honduras and Nicaragua. Using virologic data from each country's national influenza centre, rainfall from the Tropical Rainfall Measuring Mission and air temperature and specific humidity data from the Global Land Data Assimilation System, we applied logistic regression methods for each of the five sub-national locations studied. Influenza activity was represented by the weekly proportion of respiratory specimens that tested positive for influenza. The models were adjusted for the potentially confounding co-circulating respiratory viruses, seasonality and previous weeks' influenza activity. We found that influenza activity was proportionally associated (P<0.05) with specific humidity in all locations [odds ratio (OR) 1.21-1.56 per g/kg], while associations with temperature (OR 0.69-0.81 per °C) and rainfall (OR 1.01-1.06 per mm/day) were location-dependent. Among the meteorological parameters, specific humidity had the highest contribution (~3-15%) to the model in all but one location. As model validation, we estimated influenza activity for periods, in which the data was not used in training the models. The correlation coefficients between the estimates and the observed were ≤0.1 in 2 locations and between 0.6-0.86 in three others. In conclusion, our study revealed a proportional association between influenza activity and specific humidity in selected areas from the three Central America countries.

Associations between Meteorological Parameters and Influenza Activity in Berlin (Germany), Ljubljana (Slovenia), Castile and León (Spain) and Israeli Districts.

BACKGROUND: Studies in the literature have indicated that the timing of seasonal influenza epidemic varies across latitude, suggesting the involvement of meteorological and environmental conditions in the transmission of influenza. In this study, we investigated the link between meteorological parameters and influenza activity in 9 sub-national areas with temperate and subtropical climates: Berlin (Germany), Ljubljana (Slovenia), Castile and León (Spain) and all 6 districts in Israel. METHODS: We estimated weekly influenza-associated influenza-like-illness (ILI) or Acute Respiratory Infection (ARI) incidence to represent influenza activity using data from each country's sentinel surveillance during 2000-2011 (Spain) and 2006-2011 (all others). Meteorological data was obtained from ground stations, satellite and assimilated data. Two generalized additive models (GAM) were developed, with one using specific humidity as a covariate and another using minimum temperature. Precipitation and solar radiation were included as additional covariates in both models. The models were adjusted for previous weeks' influenza activity, and were trained separately for each study location. RESULTS: Influenza activity was inversely associated (p<0.05) with specific humidity in all locations. Minimum temperature was inversely associated with influenza in all 3 temperate locations, but not in all subtropical locations. Inverse associations between influenza and solar radiation were found in most locations. Associations with precipitation were location-dependent and inconclusive. We used the models to estimate influenza activity a week ahead for the 2010/2011 period which was not used in training the models. With exception of Ljubljana and Israel's Haifa District, the models could closely follow the observed data especially during the start and the end of epidemic period. In these locations, correlation coefficients between the observed and estimated ranged between 0.55 to 0.91and the model-estimated influenza peaks were within 3 weeks from the observations. CONCLUSION: Our study demonstrated the significant link between specific humidity and influenza activity across temperate and subtropical climates, and that inclusion of meteorological parameters in the surveillance system may further our understanding of influenza transmission patterns.

The role of temperature and humidity on seasonal influenza in tropical areas: Guatemala, El Salvador and Panama, 2008-2013.

BACKGROUND: The role of meteorological factors on influenza transmission in the tropics is less defined than in the temperate regions. We assessed the association between influenza activity and temperature, specific humidity and rainfall in 6 study areas that included 11 departments or provinces within 3 tropical Central American countries: Guatemala, El Salvador and Panama. METHOD/FINDINGS: Logistic regression was used to model the weekly proportion of laboratory-confirmed influenza positive samples during 2008 to 2013 (excluding pandemic year 2009). Meteorological data was obtained from the Tropical Rainfall Measuring Mission satellite and the Global Land Data Assimilation System. We found that specific humidity was positively associated with influenza activity in El Salvador (Odds Ratio (OR) and 95% Confidence Interval of 1.18 (1.07-1.31) and 1.32 (1.08-1.63)) and Panama (OR = 1.44 (1.08-1.93) and 1.97 (1.34-2.93)), but negatively associated with influenza activity in Guatemala (OR = 0.72 (0.6-0.86) and 0.79 (0.69-0.91)). Temperature was negatively associated with influenza in El Salvador's west-central departments (OR = 0.80 (0.7-0.91)) whilst rainfall was positively associated with influenza in Guatemala's central departments (OR = 1.05 (1.01-1.09)) and Panama province (OR = 1.10 (1.05-1.14)). In 4 out of the 6 locations, specific humidity had the highest contribution to the model as compared to temperature and rainfall. The model performed best in estimating 2013 influenza activity in Panama and west-central El Salvador departments (correlation coefficients: 0.5-0.9). CONCLUSIONS/SIGNIFICANCE: The findings highlighted the association between influenza activity and specific humidity in these 3 tropical countries. Positive association with humidity was found in El Salvador and Panama. Negative association was found in the more subtropical Guatemala, similar to temperate regions. Of all the study locations, Guatemala had annual mean temperature and specific humidity that were lower than the others.

CytoSys: a tool for extracting cell-cycle-related expression dynamics from static data.

Computational models of biological processes are important building blocks in Systems Biology studies. Calibration and validation are two important steps for moving a mathematical model to a computational model. While calibration refers to finding numerical value of the coefficients such as rate constants in a mathematical model, validation refers to verifying that the calibrated model behaves the same as the biological system under previously unseen conditions such as environmental changes (e.g., drug treatment) or mutations. In lieu of direct measurements of rate constants, modeling of the molecular mechanisms that govern biological behaviors may be able to use dynamic expression profiles of reactant biomolecules for calibration. For validation, similar data, obtained under new conditions, are probably better than direct measurements of rate constants. In any case, direct measurement of rate constants is almost always impractical and difficult or impossible. Here, we show a computer-assisted methodology to extract embedded dynamic profiles of cell-cycle proteins from statically sampled, multivariate cytometry data guided by heuristics assembled from canonical cell-cycle knowledge. The methodology is implemented using standard "list mode" cytometry data-processing software followed by CytoSys - a software tool with an easy-to-use graphical interface. We demonstrate the use of CytoSys with a case study of exponentially growing, human erythroleukemia cells and extract the dynamic expression profiles of cyclin A for calibrating an existing deterministic mathematical model of the cell cycle.

Towards malaria risk prediction in Afghanistan using remote sensing.

BACKGROUND: Malaria is a significant public health concern in Afghanistan. Currently, approximately 60% of the population, or nearly 14 million people, live in a malaria-endemic area. Afghanistan's diverse landscape and terrain contributes to the heterogeneous malaria prevalence across the country. Understanding the role of environmental variables on malaria transmission can further the effort for malaria control programme. METHODS: Provincial malaria epidemiological data (2004-2007) collected by the health posts in 23 provinces were used in conjunction with space-borne observations from NASA satellites. Specifically, the environmental variables, including precipitation, temperature and vegetation index measured by the Tropical Rainfall Measuring Mission and the Moderate Resolution Imaging Spectoradiometer, were used. Regression techniques were employed to model malaria cases as a function of environmental predictors. The resulting model was used for predicting malaria risks in Afghanistan. The entire time series except the last 6 months is used for training, and the last 6-month data is used for prediction and validation. RESULTS: Vegetation index, in general, is the strongest predictor, reflecting the fact that irrigation is the main factor that promotes malaria transmission in Afghanistan. Surface temperature is the second strongest predictor. Precipitation is not shown as a significant predictor, as it may not directly lead to higher larval population. Autoregressiveness of the malaria epidemiological data is apparent from the analysis. The malaria time series are modelled well, with provincial average R2 of 0.845. Although the R2 for prediction has larger variation, the total 6-month cases prediction is only 8.9% higher than the actual cases. CONCLUSIONS: The provincial monthly malaria cases can be modelled and predicted using satellite-measured environmental parameters with reasonable accuracy. The Third Strategic Approach of the WHO EMRO Malaria Control and Elimination Plan is aimed to develop a cost-effective surveillance system that includes forecasting, early warning and detection. The predictive and early warning capabilities shown in this paper support this strategy.

Modeling and predicting seasonal influenza transmission in warm regions using climatological parameters.

BACKGROUND: Influenza transmission is often associated with climatic factors. As the epidemic pattern varies geographically, the roles of climatic factors may not be unique. Previous in vivo studies revealed the direct effect of winter-like humidity on air-borne influenza transmission that dominates in regions with temperate climate, while influenza in the tropics is more effectively transmitted through direct contact. METHODOLOGY/PRINCIPAL FINDINGS: Using time series model, we analyzed the role of climatic factors on the epidemiology of influenza transmission in two regions characterized by warm climate: Hong Kong (China) and Maricopa County (Arizona, USA). These two regions have comparable temperature but distinctly different rainfall. Specifically we employed Autoregressive Integrated Moving Average (ARIMA) model along with climatic parameters as measured from ground stations and NASA satellites. Our studies showed that including the climatic variables as input series result in models with better performance than the univariate model where the influenza cases depend only on its past values and error signal. The best model for Hong Kong influenza was obtained when Land Surface Temperature (LST), rainfall and relative humidity were included as input series. Meanwhile for Maricopa County we found that including either maximum atmospheric pressure or mean air temperature gave the most improvement in the model performances. CONCLUSIONS/SIGNIFICANCE: Our results showed that including the environmental variables generally increases the prediction capability. Therefore, for countries without advanced influenza surveillance systems, environmental variables can be used for estimating influenza transmission at present and in the near future.

Overdenture - implants versus teeth - quality of life and objective therapy evaluation.

An overdenture is a complete or removable partial denture that has one or more tooth roots or implants to provide a support. The study compares two types of prosthodontic treatment - overdenture supported by remained own teeth with ball attachments and that held by implants. The cohort of 35 patients (recall from 1 to 5 years) was evaluated. When subjectively and objectively assessed no significant difference between both groups was observed.

The role of dynamic stimulation pattern in the analysis of bistable intracellular networks.

Bistable systems play an important role in the functioning of living cells. Depending on the strength of the necessary positive feedback one can distinguish between (irreversible) "one-way switch" or (reversible) "toggle-switch" type behavior. Besides the well- established steady-state properties, some important characteristics of bistable systems arise from an analysis of their dynamics. We demonstrate that a supercritical stimulus amplitude is not sufficient to move the system from the lower (off-state) to the higher branch (on-state) for either a step or a pulse input. A switching surface is identified for the system as a function of the initial condition, input pulse amplitude and duration (a supercritical signal). We introduce the concept of bounded autonomy for single level systems with a pulse input. Towards this end, we investigate and characterize the role of the duration of the stimulus. Furthermore we show, that a minimal signal power is also necessary to change the steady state of the bistable system. This limiting signal power is independent of the applied stimulus and is determined only by systems parameters. These results are relevant for the design of experiments, where it is often difficult to create a defined pattern for the stimulus. Furthermore, intracellular processes, like receptor internalization, do manipulate the level of stimulus such that level and duration of the stimulus is conducive to characteristic behavior.

Complex systems biology approach to understanding coordination of JAK-STAT signaling.

In this work, we search for coordination as an organizing principle in a complex signaling system using a multilevel hierarchical paradigm. The objective is to explain the underlying mechanism of Interferon (IFN(gamma)) induced JAK-STAT (specifically JAK1/JAK2-STAT1) pathway behavior. Starting with a mathematical model of the pathway from the literature, we modularize the system using biological knowledge via principles of biochemical cohesion, biological significance, and functionality. The modularized system is then used as a basis for in silico inhibition, knockdown/deletion and perturbation experiments to discover a coordination mechanism. Our analysis shows that a module representing the SOCS1 complex can be identified as the coordinator. Analysis of the coordinator can then be used for the selection of biological experiments for the discovery of 'soft' molecular drug targets, that could lead to the development of improved therapeutics. The coordinator identified is also being investigated to determine its relationship to pathological conditions.