Premature Judicial Termination of Non-Spendthrift Trusts: Reconciling a Dead Settlor\u27s Intent with a Living Beneficiary\u27s Needs

Section I of this comment examines the historical background of the Claflin doctrine. Section II discusses Texas cases applying the Claflin doctrine. Section III critically analyzes Section 112.054 which restricts premature trust termination. Section IV proposes adopting an amendment to the Texas Property Code to permit premature judicial termination of a non-spendthrift trust if all beneficiaries are sui juris and consent

Principal factors that determine the extension of detection range in molecular beacon aptamer/conjugated polyelectrolyte bioassays.

A strategy to extend the detection range of weakly-binding targets is reported that takes advantage of fluorescence resonance energy transfer (FRET)-based bioassays based on molecular beacon aptamers (MBAs) and cationic conjugated polyelectrolytes (CPEs). In comparison to other aptamer-target pairs, the aptamer-based adenosine triphosphate (ATP) detection assays are limited by the relatively weak binding between the two partners. In response, a series of MBAs were designed that have different stem stabilities while keeping the constant ATP-specific aptamer sequence in the loop part. The MBAs are labeled with a fluorophore and a quencher at both termini. In the absence of ATP, the hairpin MBAs can be opened by CPEs via a combination of electrostatic and hydrophobic interactions, showing a FRET-sensitized fluorophore signal. In the presence of ATP, the aptamer forms a G-quadruplex and the FRET signal decreases due to tighter contact between the fluorophore and quencher in the ATP/MBA/CPE triplex structure. The FRET-sensitized signal is inversely proportional to [ATP]. The extension of the detection range is determined by the competition between opening of the ATP/MBA G-quadruplex by CPEs and the composite influence by ATP/aptamer binding and the stem interactions. With increasing stem stability, the weak binding of ATP and its aptamer is successfully compensated to show the resistance to disruption by CPEs, resulting in a substantially broadened detection range (from millimolar up to nanomolar concentrations) and a remarkably improved limit of detection. From a general perspective, this strategy has the potential to be extended to other chemical- and biological-assays with low target binding affinity

Implementation of surface soil moisture data assimilation with watershed scale distributed hydrological model

This paper aims to investigate how surface soil moisture data assimilation affects each hydrologic process and how spatially varying inputs affect the potential capability of surface soil moisture assimilation at the watershed scale. The Ensemble Kalman Filter (EnKF) is coupled with a watershed scale, semi-distributed hydrologic model, the Soil and Water Assessment Tool (SWAT), to assimilate surface (5 cm) soil moisture. By intentionally setting inaccurate precipitation with open loop and EnKF scenarios in a synthetic experiment, the capability of surface soil moisture assimilation to compensate for the precipitation errors were examined. Results show that daily assimilation of surface soil moisture for each HRU improves model predictions especially reducing errors in surface and profile soil moisture estimation. Almost all hydrological processes associated with soil moisture are also improved with decreased root mean square error (RMSE) values through the EnKF scenario. The EnKF does not produce as much a significant improvement in streamflow predictions as compared to soil moisture estimates in the presence of large precipitation errors and the limitations of the infiltration–runoff model mechanism. Distributed errors of the soil water content also show the benefit of surface soil moisture assimilation and the influences of spatially varying inputs such as soil and landuse types. Thus, soil moisture update through data assimilation can be a supplementary way to overcome the errors created by inaccurate rainfall. Even though this synthetic study shows the potential of remotely sensed surface soil moisture measurements for applications of watershed scale water resources management, future studies are necessary that focus on the use of real-time observational data

Application of data assimilation with the Root Zone Water Quality Model for soil moisture profile estimation in the upper Cedar Creek, Indiana

Data assimilation techniques have been proven as an effective tool to improve model forecasts by combining information about observed variables in many areas. This article examines the potential of assimilating surface soil moisture observations into a field-scale hydrological model, the Root Zone Water Quality Model, to improve soil moisture estimation. The Ensemble Kalman Filter (EnKF), a popular data assimilation technique for nonlinear systems, was applied and compared with a simple direct insertion method. In situ soil moisture data at four different depths (5, 20, 40, and 60 cm) from two agricultural fields (AS1 and AS2) in northeastern Indiana were used for assimilation and validation purposes. Through daily update, the EnKF improved soil moisture estimation compared with the direct insertion method and model results without assimilation, having more distinct improvement at the 5 and 20 cm depths than for deeper layers (40 and 60 cm). Local vertical soil property heterogeneity in AS1 deteriorated soil moisture estimates with the EnKF. Removal of systematic bias in the forecast model was found to be critical for more successful soil moisture data assimilation studies. This study also demonstrates that a more frequent update generally contributes in enhancing the open loop simulation; however, large forecasting error can prevent more frequent update from providing better results. In addition, results indicate that various ensemble sizes make little difference in the assimilation results. An ensemble of 100 members produced results that were comparable with results obtained from larger ensembles

Application of observation operators for field scale soil moisture averages and variances in agricultural landscapes

Scale difference between in situ and remotely sensed soil moisture observations and model grid size has been an issue for validation of remote sensing data, soil moisture data assimilation and calibration of hydrologic models. This study aims to link two different scales of soil moisture estimates by upscaling single point measurements to field averages for representing field-scale agricultural areas (∼2 ha) located within the Upper Cedar Creek Watershed in northeastern Indiana. Several statistical methods, mainly focusing on cumulative distribution function (CDF) matching, are tested to upscale point measurements to spatially representative soil moisture. These transforming equations are termed observation operators. The CDF matching is found to be the most successful upscaling method followed by the mean relative difference method using temporally stable point measurements. This study also tests the temporal and spatial (horizontal and vertical) transferability of the different observation operators. Results indicate that the two observation operators from the CDF matching approach and the mean relative difference method using a temporally stable location are transferable in space, but not in time. Rainfall characteristic is most likely the dominant factor affecting the success of observation operator transferability. In addition, the CDF matching approach is found to be an effective method to deduce spatial variability (standard deviation) of soil moisture from single point measurements

Fluoride Induces a Volume Reduction in CA1 Hippocampal Slices Via MAP Kinase Pathway Through Volume Regulated Anion Channels

Regulation of cell volume is an important aspect of cellular homeostasis during neural activity. This volume regulation is thought to be mediated by activation of specific transporters, aquaporin, and volume regulated anion channels (VRAC). In cultured astrocytes, it was reported that swelling-induced mitogen-activated protein (MAP) kinase activation is required to open VRAC, which are thought to be important in regulatory volume decrease and in the response of CNS to trauma and excitotoxicity. It has been also described that sodium fluoride (NaF), a recognized G-protein activator and protein phosphatase inhibitor, leads to a significant MAP kinase activation in endothelial cells. However, NaF's effect in volume regulation in the brain is not known yet. Here, we investigated the mechanism of NaF-induced volume change in rat and mouse hippocampal slices using intrinsic optical signal (IOS) recording, in which we measured relative changes in intracellular and extracellular volume as changes in light transmittance through brain slices. We found that NaF (1~5 mM) application induced a reduction in light transmittance (decreased volume) in CA1 hippocampus, which was completely reversed by MAP kinase inhibitor U0126 (10 µM). We also observed that NaF-induced volume reduction was blocked by anion channel blockers, suggesting that NaF-induced volume reduction could be mediated by VRAC. Overall, our results propose a novel molecular mechanism of NaF-induced volume reduction via MAP kinase signaling pathway by activation of VRAC

Development of selective blockers for Ca2+-activated Cl- channel using Xenopus laevis oocytes with an improved drug screening strategy

<p>Abstract</p> <p>Background</p> <p>Ca²⁺-activated Cl^-channels (CaCCs) participate in many important physiological processes. However, the lack of effective and selective blockers has hindered the study of these channels, mostly due to the lack of good assay system. Here, we have developed a reliable drug screening method for better blockers of CaCCs, using the endogeneous CaCCs in <it>Xenopus laevis </it>oocytes and two-electrode voltage-clamp (TEVC) technique.</p> <p>Results</p> <p>Oocytes were prepared with a treatment of Ca²⁺ionophore, which was followed by a treatment of thapsigargin which depletes Ca²⁺stores to eliminate any contribution of Ca²⁺release. TEVC was performed with micropipette containing chelerythrine to prevent PKC dependent run-up or run-down. Under these conditions, Ca²⁺-activated Cl^-currents induced by bath application of Ca²⁺to oocytes showed stable peak amplitude when repetitively activated, allowing us to test several concentrations of a test compound from one oocyte. Inhibitory activities of commercially available blockers and synthesized anthranilic acid derivatives were tested using this method. As a result, newly synthesized <it>N</it>-(4-trifluoromethylphenyl)anthranilic acid with trifluoromethyl group (-CF₃) at <it>para </it>position on the benzene ring showed the lowest IC₅₀.</p> <p>Conclusion</p> <p>Our results provide an optimal drug screening strategy suitable for high throughput screening, and propose <it>N</it>-(4-trifluoromethylphenyl)anthranilic acid as an improved CaCC blocker.</p

Effect of Cigarette Smoke Exposure and Mutant Kras Overexpression on Pancreatic Cell Proliferation

Pancreatic cancer is the fourth leading cause of cancer‑associated mortality. The major risk factor for pancreatic cancer is cigarette smoking. Kras mutations are commonly observed in human pancreatic cancers. The present study examined the hypothesis that exposure to cigarette smoke and overexpression of a mutant Kras gene in the pancreas affects pancreatic cell proliferation in mice. Mice overexpressing the mutant Kras gene (KRasG12D) in the pancreas as well as wild‑type mice were exposed to environmental tobacco smoke for 2 weeks. Overexpression of mutant Kras increased cell proliferation in pancreatic ductal, acinar and islet cells. Notably, cigarette smoke exposure decreased cell proliferation in pancreatic ductal and acinar cells, and had no effect in islet cells. Cigarette smoke did not affect pancreatic protein levels of tumor necrosis factor (TNF)α, p53, or cyclin D1, but mutant Kras overexpression slightly decreased TNFα and p53 protein levels. Therefore, pancreatic cell proliferation in mice overexpressing mutant Kras is associated with the later development of pancreatic tumors, but effects of cigarette smoke on pancreatic cell proliferation do not provide a good model for human pancreatic carcinogenesis

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study

On the Use of a Water Balance to Evaluate Inter-annual Terrestrial ET Variability

Accurately measuring interannual variability in terrestrial evapotranspiration ET is a major challenge for efforts to detect trends in the terrestrial hydrologic cycle. Based on comparisons with annual values of terrestrial evapotranspiration derived from a terrestrial water balance analysis, past research has cast doubt on the ability of existing products to accurately capture variability. Using a variety of estimates, this analysis reexamines this conclusion and finds that estimates of variations obtained from a land surface model are more strongly correlated with independently acquired from thermal infrared remote sensing than derived from water balance considerations. This tendency is attributed to significant interannual variations in terrestrial water storage neglected by the water balance approach. Overall, results demonstrate the need to reassess perceptions concerning the skill of estimates derived from land surface models and show the value of accurate remotely sensed ET products for the validation of interannual ET