Sugar receptor response of the food-canal taste sensilla in a nectar-feeding swallowtail butterfly, Papilio xuthus

The feeding behavior in nectar-feeding insects is triggered by a sugar-receptor response in contact chemosensilla. The contact chemosensilla are distributed not only on tarsi and the outside of the proboscis but also on the inside of the food canal in Lepidoptera. Although the chemosensilla inside the food canal are assumed to detect sweet taste during the passage of nectar through the food canal, their electrophysiological function has received little attention. In the nectar-feeding Asian swallowtail butterfly, Papilio xuthus (Lepidoptera: Papilionidae), we found 15- to 30-μm-long sensilla neatly lined up along the inside galea wall, which forms the food canal in the proboscis. The receptor neurons of these sensilla responded to sucrose. We hypothesized that starch and sucrose compete with each other for a taste receptor site on the sensilla. When we added starch and sucrose to the food-canal sensilla, the electrophysiological responses of food-canal sensilla were inhibited in parallel with the food-sucking behavior of the butterflies. These results suggest that the food-canal sensilla are involved in the behavioral control of nectar-sucking in this butterfly species.     

H and O isotopic differences in typhon and urban-induced heavy rain in Tokyo

Stable isotope ratios of hydrogen and oxygen of water are useful tracers of the hydrological cycle. For example, isotopes monitor the evapotranspiration in vegetated areas, local snow ice processes and stream water flow processes. δ¹⁸O and δD in rainwater reflect the processes of evaporation, condensation and precipitation. Heavy rains thus modify the stable isotope ratio of ground water, stream water and transpiration water vapor. However, the controlling factors of δ¹⁸O and δD are not clear. Here we analyzed the inorganic ion concentration and stable isotope ratio in 38 normal rainwater and 15 heavy rainwater samples were collected in Shinjuku, Tokyo, Japan, during four years from October 2012 to December 2015. Results show a decrease in δ¹⁸O and δD values with the total rainfall amount, thus highlighting the amount effect. δ¹⁸O and δD volume-weighted mean values in typhoon heavy rain were higher than the values estimated from amount effect, whereas δ¹⁸O and δD volume-weighted mean values in urban-induced heavy rain were lower. Typhoon heavy rain has high Na⁺ ratio and stable isotope ratios, while urban-induced heavy rain has low Na⁺ ratio and stable isotope ratio.     

Characterization of the genes involved in nitrogen cycling in wastewater treatment plants using DNA microarray and most probable number-PCR

To improve nitrogen removal performance of wastewater treatment plants (WWTPs), it is essential to understand the behavior of nitrogen cycling communities, which comprise various microorganisms. This study characterized the quantity and diversity of nitrogen cycling genes in various processes of municipal WWTPs by employing two molecular-based methods:most probable number-polymerase chain reaction (MPN-PCR) and DNA microarray. MPN-PCR analysis revealed that gene quantities were not statistically different among processes, suggesting that conventional activated sludge processes (CAS) are similar to nitrogen removal processes in their ability to retain an adequate population of nitrogen cycling microorganisms. Furthermore, most processes in the WWTPs that were researched shared a pattern:the nirS and the bacterial amoA genes were more abundant than the nirK and archaeal amoA genes, respectively. DNA microarray analysis revealed that several kinds of nitrification and denitrification genes were detected in both CAS and anaerobic-oxic processes (AO), whereas limited genes were detected in nitrogen removal processes. Results of this study suggest that CAS maintains a diverse community of nitrogen cycling microorganisms; moreover, the microbial communities in nitrogen removal processes may be specific.

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Spiroplasma infection causes either early or late male killing in <Emphasis Type="Italic">Drosophila</Emphasis>, depending on maternal host age

Symbiont-induced male-killing phenotypes have been found in a variety of insects. Conventionally, these phenotypes have been divided into two categories according to the timing of action: early male killing at embryonic stages and late male killing at late larval stages. In Drosophila species, endosymbiotic bacteria of the genus Spiroplasma have been known to cause early male killing. Here, we report that a spiroplasma strain normally causing early male killing also induces late male killing depending on the maternal host age: male-specific mortality of larvae and pupae was more frequently observed in the offspring of young females. As the lowest spiroplasma density and occasional male production were also associated with newly emerged females, we proposed the density-dependent hypothesis for the expression of early and late male-killing phenotypes. Our finding suggested that (1) early and late male-killing phenotypes can be caused by the same symbiont and probably by the same mechanism; (2) late male killing may occur as an attenuated expression of early male killing; (3) expression of early and late male-killing phenotypes may be dependent on the symbiont density, and thus, could potentially be affected by the host immunity and regulation; and (4) early male killing and late male killing could be alternative strategies adopted by microbial reproductive manipulators.     

The effect of the increase in urban temperature on the concentration of photochemical oxidants

An atmospheric dispersion model, where the inputs of meteorological field were calculated using a meteorological model, was used to reproduce the observed air pollution conditions for the typical fine day in summer period, especially the concentration of the photochemical oxidants. As well, the effects of an increase in the urban temperature and VOC emissions on the concentration of photochemical oxidants were also considered. The following conclusions were drawn.The observed air pollution levels were well modeled by the atmospheric dispersion model using in this study, although modeled NO levels were slightly lower than the observed levels. An analysis of the temperature data showed that a 1 °C increase in temperature leads to a maximal photochemical oxidant concentration of 5.3 ppb, which is an increase of 11%. Additionally, the effect on the photochemical oxidant concentration due to an increase in the vegetation-derived VOCs was more than double the effect due to an increase in the photochemical reactions. It was found that the temperature and photochemical oxidant concentration were linearly related up to a temperature increase of 3 °C. When the temperature increases up to 3 °C, the concentration of photochemical oxidants increases by 19 ppb. An analysis of the effect of vegetation-derived VOCs on photochemical oxidant concentrations showed that, the concentration of photochemical oxidants was 30 ppb higher in the afternoon by the effect of vegetation-derived VOCs, so even in metropolitan areas with relatively little vegetation, vegetation-derived VOCs have a strong impact on photochemical oxidant concentrations.     

Effects of a composition change of ordinary Portland cement on waste utilization and CO2 emissions in Japan

Journal of Material Cycles and Waste Management - This paper estimates the effects of a composition change of ordinary Portland cement on waste utilization and CO2 emissions in the Japanese cement...     

A simple method to harness DC (direct current) electrical energy generated by bacterial activity

We developed a new system for collecting electrons generated by bacterial activity to supply DC (direct current) electrical energy. This system used eight titanium sub-electrodes (surface area of each sub-electrode: 189 cm²) connected to one central main titanium electrode (surface area of electrode: 1571 cm²). The distance between each sub-electrode and the main electrode was 30 cm. In an initial experiment, we collected electrons during composting cattle excreta, which was mixed with a commercially available microbial compost activator/starter. We analysed the relationships between the composting temperature and electrical current and voltage. Electrons were effectively collected and used successfully to obtain DC electrical energy. Generation of a stable voltage of approximately 0.5 V was clearly observed. This voltage was not related to compost temperature; however, the generated electrical current increased and decreased with compost temperature. The method was then used in a second experiment to collect electrons generated by bacterial activity in an agricultural field (area: 48 m²). Electrons in the field were effectively collected, and we measured a stable voltage of approximately 1.1 V and a stable current of approximately 0.7 mA. The system has the advantages of being simple, easily maintained, inexpensive, and applicable to large-scale agricultural fields.     

Bayesian Modeling of Enteric Virus Density in Wastewater Using Left-Censored Data

Stochastic models are used to express pathogen density in environmental samples for performing microbial risk assessment with quantitative uncertainty. However, enteric virus density in water often falls below the quantification limit (non-detect) of the analytical methods employed, and it is always difficult to apply stochastic models to a dataset with a substantially high number of non-detects, i.e., left-censored data. We applied a Bayesian model that is able to model both the detected data (detects) and non-detects to simulated left-censored datasets of enteric virus density in wastewater. One hundred paired datasets were generated for each of the 39 combinations of a sample size and the number of detects, in which three sample sizes (12, 24, and 48) and the number of detects from 1 to 12, 24 and 48 were employed. The simulated observation data were assigned to one of two groups, i.e., detects and non-detects, by setting values on the limit of quantification to obtain the assumed number of detects for creating censored datasets. Then, the Bayesian model was applied to the censored datasets, and the estimated mean and standard deviation were compared to the true values by root mean square deviation. The difference between the true distribution and posterior predictive distribution was evaluated by Kullback–Leibler (KL) divergence, and it was found that the estimation accuracy was strongly affected by the number of detects. It is difficult to describe universal criteria to decide which level of accuracy is enough, but eight or more detects are required to accurately estimate the posterior predictive distributions when the sample size is 12, 24, or 48. The posterior predictive distribution of virus removal efficiency with a wastewater treatment unit process was obtained as the log ratio posterior distributions between the posterior predictive distributions of enteric viruses in untreated wastewater and treated wastewater. The KL divergence between the true distribution and posterior predictive distribution of virus removal efficiency also depends on the number of detects, and eight or more detects in a dataset of treated wastewater are required for its accurate estimation.