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Alternative pre-mRNA splicing is often jointly controlled by multiple splicing factors. Here Muto and colleagues elucidate the structural basis for cooperative RNA recognition by two splicing regulators required for tissue-specific expression of C. elegans FGFR. Tissue-specific alternative pre-mRNA splicing is often cooperatively regulated by multiple splicing factors, but the structural basis of cooperative RNA recognition is poorly understood. In Caenorhabditis elegans , ligand binding specificity of fibroblast growth factor receptors (FGFRs) is determined by mutually exclusive alternative splicing of the sole FGFR gene, egl-15 . Here we determined the solution structure of a ternary complex of the RNA-recognition motif (RRM) domains from the RBFOX protein ASD-1, SUP-12 and their target RNA from egl-15 . The two RRM domains cooperatively interact with the RNA by sandwiching a G base to form the stable complex. Multichromatic fluorescence splicing reporters confirmed the requirement of the G and the juxtaposition of the respective cis elements for effective splicing regulation in vivo . Moreover, we identified a new target for the heterologous complex through an element search, confirming the functional significance of the intermolecular coordination.

The dual isotope approach using the stable isotope ratios of nitrate nitrogen (δ15NNO3) and oxygen (δ18ONO3) is a strong tool for identifying the history of nitrate in various environments. Basically, a rapid procedure for determining δ15NNO3 and δ18ONO3 values is required to analyze many more samples quickly and thus save on the operational costs of isotope-ratio mass spectrometry (IRMS). We developed a new rapid procedure to save time by pre-treating consecutive samples of nitrous oxide microbially converted from nitrate before IRMS determination. By controlling two six-port valves of the pre-treatment system separately, IRMS determination of the current sample and backflush during the next sample pre-treatment period could be conducted simultaneously. A set of 89 samples was analyzed precisely during a 25-h continuous run (17 min per sample), giving the fastest reported processing time, and simultaneously reducing liquid nitrogen and carrier helium gas consumption by 35%. Application of the procedure to an irrigated rice paddy watershed suggested that nitrate concentrations in river waters decreased in a downstream direction, mainly because of the mixing of nitrate from different sources, without distinct evidence of denitrification. Our procedure should help with more detailed studies of nitrate formation processes in watersheds.

The soil gas diffusion coefficient (DP) and its dependency on air‐filled porosity (ε) govern most gas diffusion‐reaction processes in soil. Accurate DP(ε) prediction models for undisturbed soils are needed in vadose zone transport and fate models. The objective of this paper was to develop a DP(ε) model with lower input parameter requirement and similar prediction accuracy as recent soil‐type dependent models. Combining three gas diffusivity models: (i) a general power‐law DP(ε) model, (ii) the classical Buckingham (1904) model for DP at air saturation, and (iii) a recent macroporosity dependent model for DP at −100 cm H2O of soil–water matric potential (ψ), yielded a single equation to predict DP as a function of the actual ε, the total porosity (Φ), and the macroporosity (ε100; defined as the air‐filled porosity at ψ = −100 cm H2O). The new model, termed the three‐porosity model (TPM), requires only one point (at −100 cm H2O) on the soil–water characteristic curve (SWC), compared with recent DP(ε) models that require knowledge of the entire SWC. The DP(ε) was measured at different ψ on undisturbed soil samples from dark‐red Latosols (Brazil) and Yellow soils (Japan), representing different tillage intensities. The TPM and five other DP(ε) models were tested against the new data (17 soils) and data from the literature for additional 43 undisturbed soils. The new TPM performed equally well (root mean square error [RMSE] in relative gas diffusivity <0.027) as recent SWC‐dependent DP(ε) models and better than typically used soil type independent models.

The dual isotope approach using the stable isotope ratios of nitrate nitrogen ( delta 15NNO3) and oxygen ( delta 18ONO3) is a strong tool for identifying the history of nitrate in various environments. Basically, a rapid procedure for determining delta 15NNO3 and delta 18ONO3 values is required to analyze many more samples quickly and thus save on the operational costs of isotope-ratio mass spectrometry (IRMS). We developed a new rapid procedure to save time by pre-treating consecutive samples of nitrous oxide microbially converted from nitrate before IRMS determination. By controlling two six-port valves of the pre-treatment system separately, IRMS determination of the current sample and backflush during the next sample pre-treatment period could be conducted simultaneously. A set of 89 samples was analyzed precisely during a 25-h continuous run (17 min per sample), giving the fastest reported processing time, and simultaneously reducing liquid nitrogen and carrier helium gas consumption by 35%. Application of the procedure to an irrigated rice paddy watershed suggested that nitrate concentrations in river waters decreased in a downstream direction, mainly because of the mixing of nitrate from different sources, without distinct evidence of denitrification. Our procedure should help with more detailed studies of nitrate formation processes in watersheds.

The soil gas diffusion coefficient (D(P)) and its dependency on air-filled porosity (epsilon) govern most gas diffusion-reaction processes in soil. Accurate D(P)(epsilon) prediction models for undisturbed soils are needed in vadose zone transport and fate models. The objective of this paper was to develop a D(P)(epsilon) model with lower input parameter requirement and similar prediction accuracy as recent soil-type dependent models. Combining three gas diffusivity models: (i) a general power-law D(P)(epsilon) model, (ii) the classical Buckingham (1904) model for D(P) at air saturation, and (iii) a recent macroporosity dependent model for D(P) at -100 cm H2O of soil-water matric potential (psi), yielded a single equation to predict D(P) as a function of the actual epsilon, the total porosity (phi), and the macroporosity (epsilon100; defined as the air-filled porosity at psi = -100 cm H2O). The new model, termed the three-porosity model (TPM), requires only one point (at -100 cm H2O) on the soil-water characteristic curve (SWC), compared with recent D(P)(epsilon) models that require knowledge of the entire SWC. The D(P)(epsilon) was measured at different psi on undisturbed soil samples from dark-red Latosols (Brazil) and Yellow soils (Japan), representing different tillage intensities. The TPM and five other D(P)(epsilon) models were tested against the new data (17 soils) and data from the literature for additional 43 undisturbed soils. The new TPM performed equally well (root mean square error [RMSE] in relative gas diffusivity <0.027) as recent SWC-dependent D(P)(epsilon) models and better than typically used soil type independent models.

Soil‐water‐characteristic‐dependent (SWC‐dependent) models to predict the gas diffusion coefficient, D P , in undisturbed soil have only been tested within limited ranges of pore‐size distribution and total porosity. Andisols (volcanic ash soils) exhibit unusually high porosities and water retention properties. The Campbell SWC model and two Campbell SWC‐based models for predicting D P in undisturbed soil were tested against SWC and D P data for 18 Andisols and four Gray‐lowland (paddy field) soils from Japan. The Campbell model accurately described SWC data for all 22 soils within the matric potential range from ≈ −10 to −15000 cm H 2 O. The SWC‐dependent Buckingham‐Burdine‐Campbell (BBC) gas diffusivity model predicted D P data well within the same matric potential range for the 18 Andisols. The BBC model showed a minor but systematic underprediction of D P for three out of the four Gray‐lowland soils, likely due to a blocky soil structure with internal fissures. A recent D P model that also takes into account macroporosity performed nearly as well as the BBC model. However, D P in the macropore region (air‐filled pores >30 μm) was consistently underpredicted, likely due to high continuity of the macropore system in both Andisols and Gray‐lowland soils. In agreement with previous model tests for 21 European soils (representing lower porosities and water retention properties), both SWC‐dependent D P models gave better predictions for the 22 Japanese soils than soil‐type independent models. Combining D P and SWC data, a so‐called gas diffusion fingerprint (GDF) plot to describe soil aeration potential is proposed.

Soil air permeability (k a ) governs convective air and gas transport in soil. The increased use of soil venting systems during vadose zone remediation at polluted soil sites has created a renewed interest in k a and its dependency on soil type and soil air‐filled porosity (ε). Predictive k a (ε) models have only been tested within limited ranges of pore‐size distribution and total porosity. Andisols (volcanic ash soils) exhibit unusually high porosities and water retention properties. In this study, measurements of k a (ε) on 16 undisturbed Andisols from three locations in Japan were carried out in the soil matric potential interval from −10 cm H 2 O (near water saturation) to −15000 cm H 2 O (wilting point). Two simple power‐function k a (ε) models, both with measured k a at −100 cm H 2 O as a reference point, gave similar and good predictions of k a (ε) between −10 and −1000 cm H 2 O. For one location comprising finely textured and humic Andisols, both models largely underpredicted k a (ε) in dry soil (<−3000 cm H 2 O), suggesting a sudden occurrence of highly connected air‐filled pore networks during drainage. For the two other locations, the models satisfactorily predicted k a also in dry soil. Using recently published data for gas diffusivity and soil‐water retention together with the k a data in the Millington and Quirk (1964) fluid flow model, a plot of equivalent pore diameter as a function of soil matric potential was made for each soil. This plot, labeled a soil structure fingerprint (SSF), proved useful for illustrating effects of soil cultivation and high organic matter content on soil structure.

Soil‐water‐characteristic‐dependent (SWC‐dependent) models to predict the gas diffusion coefficient, DP, in undisturbed soil have only been tested within limited ranges of pore‐size distribution and total porosity. Andisols (volcanic ash soils) exhibit unusually high porosities and water retention properties. The Campbell SWC model and two Campbell SWC‐based models for predicting DP in undisturbed soil were tested against SWC and DP data for 18 Andisols and four Gray‐lowland (paddy field) soils from Japan. The Campbell model accurately described SWC data for all 22 soils within the matric potential range from ≈ −10 to −15000 cm H2O. The SWC‐dependent Buckingham‐Burdine‐Campbell (BBC) gas diffusivity model predicted DP data well within the same matric potential range for the 18 Andisols. The BBC model showed a minor but systematic underprediction of DP for three out of the four Gray‐lowland soils, likely due to a blocky soil structure with internal fissures. A recent DP model that also takes into account macroporosity performed nearly as well as the BBC model. However, DP in the macropore region (air‐filled pores >30 μm) was consistently underpredicted, likely due to high continuity of the macropore system in both Andisols and Gray‐lowland soils. In agreement with previous model tests for 21 European soils (representing lower porosities and water retention properties), both SWC‐dependent DP models gave better predictions for the 22 Japanese soils than soil‐type independent models. Combining DP and SWC data, a so‐called gas diffusion fingerprint (GDF) plot to describe soil aeration potential is proposed.

Soil air permeability (ka) governs convective air and gas transport in soil. The increased use of soil venting systems during vadose zone remediation at polluted soil sites has created a renewed interest in ka and its dependency on soil type and soil air‐filled porosity (ε). Predictive ka(ε) models have only been tested within limited ranges of pore‐size distribution and total porosity. Andisols (volcanic ash soils) exhibit unusually high porosities and water retention properties. In this study, measurements of ka(ε) on 16 undisturbed Andisols from three locations in Japan were carried out in the soil matric potential interval from −10 cm H2O (near water saturation) to −15000 cm H2O (wilting point). Two simple power‐function ka(ε) models, both with measured ka at −100 cm H2O as a reference point, gave similar and good predictions of ka(ε) between −10 and −1000 cm H2O. For one location comprising finely textured and humic Andisols, both models largely underpredicted ka(ε) in dry soil (<−3000 cm H2O), suggesting a sudden occurrence of highly connected air‐filled pore networks during drainage. For the two other locations, the models satisfactorily predicted ka also in dry soil. Using recently published data for gas diffusivity and soil‐water retention together with the ka data in the Millington and Quirk (1964) fluid flow model, a plot of equivalent pore diameter as a function of soil matric potential was made for each soil. This plot, labeled a soil structure fingerprint (SSF), proved useful for illustrating effects of soil cultivation and high organic matter content on soil structure.